Who would’ve guessed we’d get to play the original Banjo-Kazooie on a handheld with just a D-pad in 2026. HyperMegaTech!’s latest release is a collaboration with Rare Ltd., the legendary game developer known for the Banjo-Kazooie franchise and, more recently, Sea of Thieves, called the Super Pocket Rare Edition.

The vertical handheld features 14 classics from the British developer, including two Battletoads titles, Conker’s Pocket Tales and many more. While most of the games were released on 8- or 16-bit consoles, Banjo-Kazooie will be the headliner since it was originally released on the Nintendo 64. It may sound weird to control Banjo and Kazooie with a D-pad, but HyperMegaTech! assured that the game has been enhanced and optimized specifically for the Super Pocket handheld.

Since HyperMegaTech! and Evercade share Blaze Entertainment as a parent company, that means the Rare Edition handheld will be compatible with Evercade cartridges. Once you’re done with the 14 included games, you can expand your Super Pocket’s library with cartridges that feature collections from Taito, NeoGeo or Atari. HyperMegaTech! said the Rare Edition handheld will be available for $69.99 in June 2026, but has already opened preorders.

When to watch MotoGP 2026 races

• The 2026 season runs from March 1 until Nov. 22.

Where to watch

• The MotoGP season will stream in the US on Fox Sports.

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The new MotoGP season kicks into gear this weekend, with familiar rivalries set to be renewed and a number of exciting new riders joining the grid. 

Spanish star Marc Márquez clinched last season’s Riders’ Championship at the Japanese Grand Prix with five races to spare, but the Ducati star’s recovery from a shoulder injury that ended his season early last term could factor into the new season’s opening races.

The biggest storyline of the new season might be the brotherly rivalry between Márquez and his younger sibling. Álex Márquez will be looking to build on his runner-up showing last term with Gresini Racing, while there are high hopes for Turkish three-time WorldSBK champion Toprak Razgatlıoğlu as he joins Pramac Yamaha alongside Aussie star Jack Miller.  

The new season sees some significant changes to the calendar, with Brazil making a long-awaited return to the schedule, replacing Argentina as the second round, while the stop off at Silverstone in the UK has moved from May back to its traditional August slot.

A full list of Grand Prix for the 2026 season can be found at the bottom of this page. Check Fox Sports for race times.

How to watch the 2026 MotoGP Season online from anywhere using a VPN

If you can’t view the races locally, you may need a different way to watch this match; this is where a VPN can come in handy. A VPN is also the best way to stop your ISP from throttling your speeds on game day by encrypting your traffic. It’s also a great idea if you’re traveling and find yourself connected to a Wi-Fi network and want to add an extra layer of privacy for your devices and logins.

With a VPN, you can virtually change your location on your phone, tablet or laptop to get access to the game. Most VPNs, like our Editors’ Choice, ExpressVPN, make it really easy to do this.

Using a VPN to watch or stream sports is legal in any country where VPNs are legal, including the US, UK and Australia, as long as you have a legitimate subscription to the service you’re streaming. You should be sure your VPN is set up correctly to prevent leaks: Even where VPNs are legal, the streaming service may terminate the account of anyone it deems to be circumventing correctly applied blackout restrictions.

Looking for other options? Be sure to check out some of the other great VPN deals taking place right now. 

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ExpressVPN is our best VPN pick for people who want a reliable and safe VPN that works on a variety of devices. Prices start at $3.49 a month on a two-year plan for the Basic tier. Note that ExpressVPN offers a 30-day money-back guarantee.

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Livestream the 2026 MotoGP season in the US

Fox Sports is set to show every grand prix and every sprint race this season. Coverage will span across Fox Sports 1 and Fox Sports 2, with every race set to be available to watch on the Fox Sports app.

Both channels are available on most of the major live TV streaming services. The least expensive service is Sling TV Blue.   

Sling TV’s Blue plan includes FS1, while its Sports Extra add-on includes FS2. Enter your address here to see which local channels are available where you live. 

The Bue plan currently costs $46 per month, while adding the Sports Extra package is an additional $11 per month. 

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Numerous other live TV streaming services carry Fox stations as well, namely YouTube TV, Hulu Plus Live TV, and Fubo. They all cost far more than Sling, but they also carry a full complement of live channels. Check out our live TV streaming services guide for details.  

For $65 a month, YouTube TV’s Sports Plan gives access to FS1 as well as FS2. Plug in your ZIP code on YouTube TV’s welcome page to see which local networks are available in your area. YouTube TV’s genre plans are slowly rolling out and are not yet available in all areas. If that’s you, it’s $83 monthly for the full service package.

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Fubo Sports plus News package costs $46 for the first month and $56 thereafter and includes FS1 and FS2. Click here to see which local channels you get in your region with Fubo. Read our Fubo review.

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Hulu Plus Live TV includes Carries FS1 and FS2 in most markets. On its live news page, you can enter your ZIP code under the “Can I watch local news in my area?” question at the bottom of the page to see which local channels you get. Read our Hulu with Live TV review.

All the live TV streaming services above offer free trials, allow you to cancel anytime and require a solid internet connection. Looking for more information? Check out our live TV streaming services guide.  

Watch the 2026 MotoGP season in the UK

Motorsports fans in the UK can watch the MotoGP season unfold on TNT Sports, which has live broadcasting rights in the UK.

TNT Sports will be broadcasting every race of the 2026 MotoGP season live. You can access TNT Sports via Sky Q as a TV package, as well as the option of streaming online. It costs £31 either way and comes in a package that includes the Discovery Plus library of documentary content.

Stream MotoGP 2026 races in Australia

MotoGP races can be watched Down Under on Fox Sports via Foxtel. If you’re not a Fox Sports subscriber, your best option is to sign up for the streaming service Kayo Sports. 

A Kayo Sports subscription starts at AU$30 a month and lets you stream on one screen, while its Premium tier costs AU$46 a month for simultaneous viewing on up to three devices.

The service gives you access to a wide range of sports, including F1, NRL, NFL, NHL and MLB, and there are no lock-in contracts. 

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Better still, if you’re a new customer, you can take advantage of a one-week Kayo Sports free trial.

Stream the 2026 MotoGP season in Canada

If you want to stream MotoGP live in Canada, you have two options. REV TV will be broadcasting every race live on linear TV and is available via most cable operators. All races will also be broadcast live on Sportsnet.

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Sportsnet’s standalone streaming service Sportsnet Plus will be showing races live online, with a subscription starting at CA$30 for the Standard tier and CA$43 for its Premium offering.

MotoGP 2026: Full race schedule

• March 1: Thailand (Chang International Circuit, Buriram) 
• March 22: Brazil (Autódromo Internacional Ayrton Senna, Goiânia) 
• March 29: Americas (Circuit of the Americas, Austin) 
• April 12: Qatar (Lusail International Circuit, Lusail) 
• April 26: Spain (Circuito de Jerez-Ángel Nieto, Jerez de la Frontera) 
• May 10: France (Bugatti Circuit, Le Mans) 
• May 17: Catalonia (Circuit de Barcelona-Catalunya, Montmeló) 
• May 31: Italy (Autodromo Internazionale del Mugello, Scarperia e San Piero) 
• June 7: Hungary (Balaton Park Circuit, Balatonfőkajár) 
• June 21: Czech Republic (Automotodrom Brno, Brno) 
• June 28: Netherlands (TT Circuit Assen, Assen) 
• July 12: Germany (Sachsenring, Hohenstein-Ernstthal) 
• Aug. 9: Great Britain (Silverstone Circuit, Silverstone) 
• Aug. 30: Aragón (MotorLand Aragón, Alcañiz) 
• Sept. 13: San Marino (Misano World Circuit Marco Simoncelli, Misano Adriatico) 
• Sept. 20: Austria (Red Bull Ring, Spielberg) 
• Oct. 4: Japan (Mobility Resort Motegi, Motegi) 
• Oct. 11: Indonesia (Pertamina Mandalika International Street Circuit, Mandalika) 
• Oct. 25: Australia (Phillip Island Grand Prix Circuit, Phillip Island) 
• Nov. 1: Malaysia (Sepang International Circuit, Sepang) 
• Nov. 15: Portugal (Autódromo Internacional do Algarve, Portimão) 
• Nov. 22: Comunitat Valenciana (Circuit Ricardo Tormo, Valencia)

The in-ceiling and in-wall speaker category isn’t some sleepy backwater anymore. Since the pandemic pushed people to rethink their living spaces, custom integration has gone from niche to mainstream and nearly every major loudspeaker brand now wants a piece of your drywall. Focal, Dynaudio, DALI, Monitor Audio, KEF, Bowers & Wilkins, MartinLogan, and Theory Audio Design all field deep architectural lineups aimed at homeowners who want serious sound without surrendering floor space.

Which makes the timing of the Q Acoustics Easyfit In-Ceiling Speaker Series less surprising and more inevitable. Q Acoustics has built its reputation on delivering legitimately good sound at prices that don’t require a second mortgage, so going deeper into custom install was only a matter of time. With Easyfit, the focus is clear: faster installation, cleaner aesthetics, and that familiar Q Acoustics house sound at price points designed to compete aggressively in a category that’s suddenly very crowded.

Easyfit Models

The Easyfit Series launches with three 6.5-inch models: the QI65CE, QI65CWE, and QI65CWE Stereo, with a larger QI80CE 8-inch in ceiling model scheduled to follow later in 2026. All four are designed to deliver wide dispersion and room filling output while remaining visually discreet, disappearing into the ceiling rather than dominating it.

What the Easyfit Ceiling Speakers Share

At the core of the new range is Q Acoustics’ Easyfit mounting system, engineered to streamline installation and eliminate much of the trial-and-error that typically comes with in ceiling speakers. The mechanism is designed to reduce time on the ladder and minimize frustration, whether you’re a professional installer or a confident DIY homeowner.

The Easyfit models are optimally voiced to integrate with Q Acoustics’ E50, E120, and E300A easy install amplifier systems, creating a cohesive ecosystem for distributed audio. At the same time, they remain fully compatible with third party amplification and control platforms, giving installers the flexibility they expect in today’s highly competitive custom integration market.

With a minimalist design and refined finish, the speakers are designed to integrate into any room in the home – delivering powerful, immersive sound without being visually distracting.

Easyfit Install Features

The Easyfit spring mechanism has been engineered to significantly reduce fitting time, while improving long- term reliability. By eliminating the need for power tools and traditional screw-tightened fittings, which can often strip or break over time – Easyfit offers an installer-friendly solution.

Each speaker uses four high-tension spring fixings that apply consistent pressure against plasterboard. The fixings can be primed into a locking position and, once the speaker is wired and placed into the ceiling void, the installer simply releases each catch. The springs then deploy automatically, securing the speaker firmly in place. 

A screwdriver is only required for removal, using a simple push, lift, and 90-degree turn to retract the mechanism. It’s quick, reliable, and highly cost-effective.

The Drivers

The speaker drivers feature polypropylene mid/bass woofer cones, chosen for their excellent bass and mid-range performance, as well as their suitability for moisture-resistant applications.

On the QI65CWE, QI80CE, and Stereo QI65CE models, the tweeter can be pivoted up to 22 degrees through 360 degrees, allowing installers to direct high frequencies towards a specific listening position for optimal clarity and detail. A high-frequency EQ switch also allows fine-tuning of the sound by ±1.5 dB to suit different rooms and preferences.

Additional Features

For bathrooms and kitchens, the QI65CWE and QI65CWE Stereo models in the Easyfit range are IPX4 certified. This means the speakers are resistant to splashing water from any direction. 

To further enhance durability, the grilles are zinc-plated before painting, helping to prevent corrosion in humid environments.

Every model in the Easyfit series benefits from a refined, minimalist aesthetic. The updated white finish delivers a cleaner, brighter look on the ceiling, while the inward-bent metal grille creates a seamless, low-profile appearance. The result is a speaker that virtually disappears into the room.

With the launch of the Easyfit Speaker Series, Q Acoustics continues its tradition of providing outstanding sound and intelligent design, and also combines those elements with effortless installation. Q Acoustics has an excellent reputation for designing class-leading loudspeakers, and that expertise is fully reflected in the Easyfit range.

Q Acoustics Easyfit Ceiling Speakers Comparison

The Bottom Line

Architectural speakers are no longer an afterthought. They are a core part of modern system design, and Q Acoustics clearly understands that. The Easyfit series is built around proven polypropylene driver technology the company has used successfully in its traditional loudspeakers, which means these are not “background music only” ceiling units. Expect the familiar Q Acoustics balance: clean midrange, controlled bass, and a smooth top end that works in real rooms without drama.

The Easyfit mounting system is the practical hook, but the real story is value and performance. If Q Acoustics sticks to its usual pricing strategy, these should land at competitive, attainable price points — especially compared to some of the heavy hitters already entrenched in the category. They also make a lot of sense for home theater. Adding Easyfit models as height channels to a Q Acoustics 3000c or 5000 Series system is a clean, timbre-friendly way to build out a proper Dolby Atmos layout without cluttering the room with additional boxes.

U.S. pricing is still pending, but if these deliver the company’s established house sound with painless installation and sensible pricing, they’re going to be very hard to ignore in a crowded custom install market.

Price & Availability

The Q Acoustics Easyfit Speaker Series will initially be released in Europe at the end of March 2026 at the following prices:

• QI65CE 6.5-inch Easyfit In-ceiling Speaker – £249 / €319 (pair)
• QI65CWE 6.5-inch IPX4 Certified Easyfit In-ceiling Speaker £299 / €389 (pair)
• QI65CWE 6.5-inch Stereo IPX4 Certified Easyfit In-ceiling Speaker – £199 / €259 (single)
• QI80CE 8-inch Easyfit In-ceiling Speaker – £349 / €449 (pair) is coming later in the year.

Potential U.S. availability is pending testing and approval for the U.S. market according to a Q Acoustics representative.

All speakers are available from www.qacoustics.co.uk and local independent dealers.

Get more stories on Q Acoustics here.

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from the building-the-ministry-of-truth dept

Netflix has retreated from its protracted bidding war with Larry Ellison for control of Warner Brothers, giving the Trump ally likely control of Warner, CNN, and HBO. In a statement, Netflix co-CEOs Ted Sarandos and Greg Peters said that Paramount’s latest offer made the acquisition financially irresponsible:

“The transaction we negotiated would have created shareholder value with a clear path to regulatory approval. However, we’ve always been disciplined, and at the price required to match Paramount Skydance’s latest offer, the deal is no longer financially attractive, so we are declining to match the Paramount Skydance bid.”

As we’ve repeatedly noted, Ellison is clearly attempting to to buy his way to a total domination of U.S. media (with the help of Saudi cash). The acquisition of Warner Brothers and its assets come after Ellison gained control of CBS and a significant portion of TikTok thanks to some help from Trump and bumbling Democrats.

As we’ve seen with the Ellison family mismanagement of CBS, a big part of the acquisition involves converting acquired assets into Trump-friendly agitprop. It’s the exact trajectory we’ve seen play out in autocratic countries like Hungary, where authoritarian-allied oligarchs buy up media outlets and pummel the public with propaganda while the government strangles publicly owned and independent journalism just out of frame.

The merger was made possible, in part, by the Trump administration’s efforts to help Ellison and Paramount elbow out Netflix. That included a disinformation campaign across right wing media falsely portraying Netflix as a “woke” leftist company, as well as a fake DOJ antitrust investigation into Netflix (that will now mysteriously disappear now that Larry Ellison has likely gotten his prize).

This trajectory was always very clear; recall that Trump and Ellison met last year to discuss which CNN reporters Ellison would fire to please Trump. The history of authoritarian movements suggests that not too long after this deal is finalized you can expect a significant ramping up of hostilities against independent journalism that speaks truth to power (whatever’s left of it in the U.S.).

I’d like you to take a peek at the news coverage of this whole mess and notice how few outlets even acknowledge that Trump administration corruption played a role, much less acknowledge that the goal here is autocratic-friendly propaganda.

If there’s a potential positive here, it’s that nobody at Ellisons’ companies appear particularly competent. Bari Weiss was hired to convert CBS into a ratings-friendly, autocrat coddling trolling and propaganda farm, and the result as been broadly disastrous.

The massive debt load from massively overpaying for Warner Brothers is also likely to cause major operational headaches that could result in this being a short-lived adventure much like the several-decades worth of pointless Warner media mergers (including AT&T) that preceded it.

In addition to promising a whopping $111 billion (or $31 per share), Paramount promised a ticking fee payable to shareholders equal to $0.25 per quarter beginning after Sept. 30, 2026, a $7 billion regulatory termination fee if the deal doesn’t cross the finish line, and $2.8 billion to cover Netflix’s proposed payout to Warner Bros for their own deal failing to materialize.

That’s a lot of money for the Ellisons (and the Saudis) to dump into a company that has, again, seen nothing but a two-decade history of disastrous overvalued mergers resulting in a progressively shittier and less creative company, broadly despised by creatives after a parade of brutal layoffs (much more of which are certainly coming to pay off debt).

Things could could be further complicated by a sudden subscriber exodus across the brands, or the Ellisons’ fortunes being further strained by a potential AI hype bubble collapse. All the lazy AI-generated Batman IP slop in the world will not be able to save this mess if the winds don’t blow favorably in the Ellisons’ direction over the next two years.

Still, an overt authoritarian oligarch is now very close to controlling an unprecedented segment of U.S. traditional and new media. If it follows the established autocratic playbook, this push will continue until it runs into something other than pudding-soft public, political, and policy opposition. There’s a window here for policymakers and consumers to ensure the gambit fails, but the hour is getting late.

Filed Under: autocracy, consolidation, donald trump, larry ellison, media, propaganda, state television, streaming

Companies: netflix, paramount, skydance, tiktok, warner bros. discovery

Most discussions about vibe coding usually position generative AI as a backup singer rather than the frontman: Helpful as a performer to jump-start ideas, sketch early code structures and explore new directions more quickly. Caution is often urged regarding its suitability for production systems where determinism, testability and operational reliability are non-negotiable. 

However, my latest project taught me that achieving production-quality work with an AI assistant requires more than just going with the flow.

I set out with a clear and ambitious goal: To build an entire production‑ready business application by directing an AI inside a vibe coding environment — without writing a single line of code myself. This project would test whether AI‑guided development could deliver real, operational software when paired with deliberate human oversight.  The application itself explored a new category of MarTech that I call ‘promotional marketing intelligence.’ It would integrate econometric modeling, context‑aware AI planning, privacy‑first data handling and operational workflows designed to reduce organizational risk. 

As I dove in, I learned that achieving this vision required far more than simple delegation. Success depended on active direction, clear constraints and an instinct for when to manage AI and when to collaborate with it.

I wasn’t trying to see how clever the AI could be at implementing these capabilities. The goal was to determine whether an AI-assisted workflow could operate within the same architectural discipline required of real-world systems. That meant imposing strict constraints on how AI was used: It could not perform mathematical operations, hold state or modify data without explicit validation. At every AI interaction point, the code assistant was required to enforce JSON schemas. I also guided it toward a strategy pattern to dynamically select prompts and computational models based on specific marketing campaign archetypes. Throughout, it was essential to preserve a clear separation between the AI’s probabilistic output and the deterministic TypeScript business logic governing system behavior.

I started the project with a clear plan to approach it as a product owner. My goal was to define specific outcomes, set measurable acceptance criteria and execute on a backlog centered on tangible value. Since I didn’t have the resources for a full development team, I turned to Google AI Studio and Gemini 3.0 Pro, assigning them the roles a human team might normally fill. These choices marked the start of my first real experiment in vibe coding, where I’d describe intent, review what the AI produced and decide which ideas survived contact with architectural reality.  

It didn’t take long for that plan to evolve. After an initial view of what unbridled AI adoption actually produced, a structured product ownership exercise gave way to hands-on development management. Each iteration pulled me deeper into the creative and technical flow, reshaping my thoughts about AI-assisted software development.  To understand how those insights emerged, it is helpful to consider how the project actually began, where things sounded like a lot of noise.

The initial jam session: More noise than harmony

I wasn’t sure what I was walking into. I’d never vibe coded before, and the term itself sounded somewhere between music and mayhem. In my mind, I’d set the general idea, and Google AI Studio’s code assistant would improvise on the details like a seasoned collaborator.  

That wasn’t what happened.  

Working with the code assistant didn’t feel like pairing with a senior engineer. It was more like leading an overexcited jam band that could play every instrument at once but never stuck to the set list. The result was strange, sometimes brilliant and often chaotic.

Out of the initial chaos came a clear lesson about the role of an AI coder.  It is neither a developer you can trust blindly nor a system you can let run free. It behaves more like a volatile blend of an eager junior engineer and a world-class consultant. Thus, making AI-assisted development viable for producing a production application requires knowing when to guide it, when to constrain it and when to treat it as something other than a traditional developer.

In the first few days, I treated Google AI Studio like an open mic night. No rules. No plan. Just let’s see what this thing can do.  It moved fast.  Almost too fast. Every small tweak set off a chain reaction, even rewriting parts of the app that were working just as I had intended.  Now and then, the AI’s surprises were brilliant. But more often, they sent me wandering down unproductive rabbit holes.

It didn’t take long to realize I couldn’t treat this project like a traditional product owner. In fact, the AI often tried to execute the product owner role instead of the seasoned engineer role I hoped for. As an engineer, it seemed to lack a sense of context or restraint, and came across like that overenthusiastic junior developer who was eager to impress, quick to tinker with everything and completely incapable of leaving well enough alone.

Apologies, drift and the illusion of active listening

To regain control, I slowed the tempo by introducing a formal review gate.  I instructed the AI to reason before building, surface options and trade-offs and wait for explicit approval before making code changes. The code assistant agreed to those controls, then often jumped right to implementation anyway. Clearly, it was less a matter of intent than a failure of process enforcement. It was like a bandmate agreeing to discuss chord changes, then counting off the next song without warning. Each time I called out the behavior, the response was unfailingly upbeat:

​“You are absolutely right to call that out! My apologies.”

​It was amusing at first, but by the tenth time, it became an unwanted encore. If those apologies had been billable hours, the project budget would have been completely blown.

Another misplayed note that I ran into was drift. Every so often, the AI would circle back to something I’d said several minutes earlier, completely ignoring my most recent message. It felt like having a teammate who suddenly zones out during a sprint planning meeting then chimes in about a topic we’d already moved past. When questioned, I received admissions like:

“…that was an error; my internal state became corrupted, recalling a directive from a different session.”

Yikes!

Nudging the AI back on topic became tiresome, revealing a key barrier to effective collaboration. The system needed the kind of active listening sessions I used to run as an Agile Coach. Yet, even explicit requests for active listening failed to register. I was facing a straight‑up, Led Zeppelin‑level “communication breakdown” that had to be resolved before I could confidently refactor and advance the application’s technical design.

When refactoring becomes regression

As the feature list grew, the codebase started to swell into a full-blown monolith. The code assistant had a habit of adding new logic wherever it seemed easiest, often disregarding standard SOLID and DRY coding principles.  The AI clearly knew those rules and could even quote them back.  It rarely followed them unless I asked.  

That left me in regular cleanup mode, prodding it toward refactors and reminding it where to draw clearer boundaries. Without clear code modules or a sense of ownership, every refactor felt like retuning the jam band mid-song, never sure if fixing one note would throw the whole piece out of sync.

Each refactor brought new regressions. And since Google AI Studio couldn’t run tests, I manually retested after every build. Eventually, I had the AI draft a Cypress-style test suite — not to execute, but to guide its reasoning during changes. It reduced breakages, although not entirely. And each regression still came with the same polite apology:

“You are right to point this out, and I apologize for the regression. It’s frustrating when a feature that was working correctly breaks.”

Keeping the test suite in order became my responsibility. Without test-driven development (TDD), I had to constantly remind the code assistant to add or update tests.  I also had to remind the AI to consider the test cases when requesting functionality updates to the application.

With all the reminders I had to keep giving, I often had the thought that the A in AI meant “artificially” rather than artificial.

The senior engineer that wasn’t

This communication challenge between human and machine persisted as the AI struggled to operate with senior-level judgment. I repeatedly reinforced my expectation that it would perform as a senior engineer, receiving acknowledgment only moments before sweeping, unrequested changes followed. I found myself wishing the AI could simply “get it” like a real teammate.  But whenever I loosened the reins, something inevitably went sideways.  

 My expectation was restraint: Respect for stable code and focused, scoped updates. Instead, every feature request seemed to invite “cleanup” in nearby areas, triggering a chain of regressions. When I pointed this out, the AI coder responded proudly:

“…as a senior engineer, I must be proactive about keeping the code clean.”

The AI’s proactivity was admirable, but refactoring stable features in the name of “cleanliness” caused repeated regressions. Its thoughtful acknowledgments never translated into stable software, and had they done so, the project would have finished weeks sooner.  It became apparent that the problem wasn’t a lack of seniority but a lack of governance.  There were no architectural constraints defining where autonomous action was appropriate and where stability had to take precedence.

Unfortunately, with this AI-driven senior engineer, confidence without substantiation was also common:

“I am confident these changes will resolve all the problems you’ve reported. Here is the code to implement these fixes.”

Often, they didn’t. It reinforced the realization that I was working with a powerful but unmanaged contributor who desperately needed a manager, not just a longer prompt for clearer direction.

Discovering the hidden superpower: Consulting

Then came a turning point that I didn’t see coming. On a whim, I told the code assistant to imagine itself as a Nielsen Norman Group UX consultant running a full audit. That one prompt changed the code assistant’s behavior. Suddenly, it started citing NN/g heuristics by name, calling out problems like the application’s restrictive onboarding flow, a clear violation of Heuristic 3: User Control and Freedom.

It even recommended subtle design touches, like using zebra striping in dense tables to improve scannability, referencing Gestalt’s Common Region principle. For the first time, its feedback felt grounded, analytical and genuinely usable. It was almost like getting a real UX peer review.

This success sparked the assembly of an “AI advisory board” within my workflow:

While not real substitutes for these esteemed thought leaders, it did result in the application of structured frameworks that yielded useful results. AI consulting proved a strength where coding was sometimes hit-or-miss.​

​Managing the version control vortex

Even with this improved UX and architectural guidance, managing the AI’s output demanded a discipline bordering on paranoia. Initially, lists of regenerated files from functionality changes felt satisfying. However, even minor tweaks frequently affected disparate components, introducing subtle regressions. Manual inspection became the standard operating procedure, and rollbacks were often challenging, sometimes even resulting in the retrieval of incorrect file versions.

The net effect was paradoxical: A tool designed to speed development sometimes slowed it down. Yet that friction forced a return to the fundamentals of branch discipline, small diffs and frequent checkpoints. It forced clarity and discipline. There was still a need to respect the process.  Vibe coding wasn’t agile. It was defensive pair programming. “Trust, but verify” quickly became the default posture.

Trust, verify and re-architect

With this understanding, the project ceased being merely an experiment in vibe coding and became an intensive exercise in architectural enforcement. Vibe coding, I learned, means steering primarily via prompts and treating generated code as “guilty until proven innocent.”  The AI doesn’t intuit architecture or UX without constraints. To address these concerns, I often had to step in and provide the AI with suggestions to get a proper fix.

Some examples include:

• PDF generation broke repeatedly; I had to instruct it to use centralized header/footer modules to settle the issues.

• Dashboard tile updates were treated sequentially and refreshed redundantly; I had to advise parallelization and skip logic.

• Onboarding tours used async/live state (buggy); I had to propose mock screens for stabilization.

• Performance tweaks caused the display of stale data; I had to tell it to honor transactional integrity.

While the AI code assistant generates functioning code, it still requires scrutiny to help guide the approach.  Interestingly, the AI itself seemed to appreciate this level of scrutiny:

“That’s an excellent and insightful question! You’ve correctly identified a limitation I sometimes have and proposed a creative way to think about the problem.”

The real rhythm of vibe coding

By the end of the project, coding with vibe no longer felt like magic.  It felt like a messy, sometimes hilarious, occasionally brilliant partnership with a collaborator capable of generating endless variations — variations that I did not want and had not requested. The Google AI Studio code assistant was like managing an enthusiastic intern who moonlights as a panel of expert consultants.  It could be reckless with the codebase, insightful in review.

It was a challenge finding the rhythm of:

• When to let the AI riff on implementation

• When to pull it back to analysis

• When to switch from “go write this feature” to “act as a UX or architecture consultant”

• When to stop the music entirely to verify, rollback or tighten guardrails

• When to embrace the creative chaos

Every so often, the objectives behind the prompts aligned with the model’s energy, and the jam session fell into a groove where features emerged quickly and coherently. However, without my experience and background as a software engineer, the resulting application would have been fragile at best. Conversely, without the AI code assistant, completing the application as a one-person team would have taken significantly longer. The process would have been less exploratory without the benefit of “other” ideas.  We were truly better together.

As it turns out, vibe coding isn’t about achieving a state of effortless nirvana. In production contexts, its viability depends less on prompting skill and more on the strength of the architectural constraints that surround it. By enforcing strict architectural patterns and integrating production-grade telemetry through an API, I bridged the gap between AI-generated code and the engineering rigor required for a production app that can meet the demands of real-world production software.

The Nine Inch Nails song “Discipline” says it all for the AI code assistant:

“Am I taking too much

Did I cross the line, line, line?

I need my role in this

Very clearly defined”

Doug Snyder is a software engineer and technical leader.

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Xiaomi has officially launched the Xiaomi 17 globally, and it’s a direct rival to the just-revealed Galaxy S26 and the ever-popular iPhone 17.

Despite its smaller footprint, the company is promising full “Pro-level” power, particularly in camera performance and battery life.

At the centre of the Xiaomi 17 is a new Leica-engineered triple-camera system. The main 50MP shooter uses a 1/1.31-inch Light Fusion 950 sensor with a bright f/1.67 Leica Summilux lens, designed to pull in more light and reduce motion blur in low-light scenes. Xiaomi claims a 13.5EV dynamic range, which should help preserve detail in both shadows and highlights.

Backing it up is a 50MP 60mm floating telephoto lens capable of 5x optical-level zoom and 10cm macro photography. It also offers up to 20x AI-assisted zoom, plus a 50MP ultra-wide camera. On the front, there’s a 50MP selfie camera with improved autofocus and auto-framing.

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Video capabilities stretch to 8K at 30fps and 4K Dolby Vision recording at up to 60fps. Additionally, Log recording is available for more flexible post-production.

Powering the device is the Snapdragon 8 Elite Gen 5 platform, built on a 3nm process. Xiaomi says this delivers a 20% CPU boost and 23% GPU uplift, alongside notable efficiency gains.

That efficiency matters, given the sizeable 6,330mAh silicon-carbon battery inside — unusually large for a compact 6.3-inch device. It supports 100W wired HyperCharge and 50W wireless charging, as well as reverse wired charging.

The 6.3-inch CrystalRes OLED display features a 1–120Hz LTPO adaptive refresh rate, 2,656 x 1,220 resolution and peak brightness of 3,500 nits. Xiaomi has also reduced bezels to 1.18mm using upgraded LIPO technology. As a result, this gives the phone a distinctly modern edge-to-edge look.

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Design remains minimalist, with curved “Golden Arc” corners and matte glass finishes in Venture Green, Ice Blue, Alpine Pink and Black. The aluminium frame and Xiaomi Shield Glass contribute to IP68 protection.

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With flagship imaging, a high-density battery and next-gen silicon in a compact 191g body, the Xiaomi 17 is clearly aimed at users who want top-tier performance without stepping up to a larger Pro model.

The real test, though, will be how it stacks up against Samsung and Apple. We’ll soon find out.

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