Software Planet Group

13/06/2026

By now, you have probably heard that the US Government has instructed Anthropic to suspend access to its latest frontier models.

We have been arguing for some time that a move of this kind was not only possible, but increasingly likely. In our view, the real question was never whether governments would intervene, but when.

Some time ago, we set out our thoughts on the logic behind this process, the challenges of regulating increasingly capable AI systems, and whether it is still possible to slow, redirect, or meaningfully control the trajectory of AI development.

You can read our perspective here:

https://softwareplanetgroup.co.uk/ai-has-escaped-the-lab/

The article ends with a question that now feels more relevant than ever: if AI has already escaped the lab, where exactly are we on that journey today?

06/05/2026

It feels like the AI race is entering a very different phase.

One of the more unexpected developments recently: Musk is reportedly allocating capacity from his 1GW Colossus data centre to Anthropic. And that looks rather significant.

Not long ago, Colossus was being positioned as infrastructure built primarily for Grok and xAI. At the same time, Musk had repeatedly criticised Anthropic publicly, often dismissing the company and its approach altogether.

But the market is moving fast.

Anthropic is seeing explosive demand for Claude, and the company clearly needs additional compute capacity to keep up. Ironically, part of that demand may now be supported by infrastructure originally intended to strengthen a direct competitor.

At the same time, Grok appears to be losing momentum.

A good example is Vending Bench - a benchmark focused on long-horizon agentic capabilities. Around the launch of Grok 4, the model scored roughly 4.6k, while Claude 4 was closer to 2k.

Today, Opus 4.7 reportedly exceeds 10k, while Grok’s progress appears far more limited.

And this may be the most important point.

AI development is starting to compound on itself. Leading labs openly discuss how their own models already assist with coding, research, evaluation pipelines and even parts of model development itself.

In other words, stronger models increasingly help build even stronger models.

Which means that once a company starts falling behind, catching up becomes exponentially harder because the leaders are accelerating at the same time.

Against that backdrop, the departure of senior engineers from xAI and the relatively quiet Grok 4.2 release without strong benchmark positioning begin to look more meaningful.

Does this mean xAI is out of the race? Probably too early to say that. Musk has repeatedly shown an ability to make unexpected moves and recover difficult situations.

But allowing a direct competitor access to your flagship infrastructure does look like a strong signal of just how intense the competition in AI has become.

And right now, Anthropic increasingly looks like one of the biggest beneficiaries of this phase of the market.

Curious to hear other views - can xAI realistically close the gap over the next 12-18 months?

27/04/2026

AI is once again reshaping how we think about product design and development.

Two new tools from major players are starting to influence not only how interfaces are created, but also how teams approach UX decisions, prototyping, and even collaboration between designers and engineers. At first glance, both solutions look impressive - but the real story sits beneath the surface.

There are subtle, yet critical differences in how they operate, what problems they actually solve, and where their limitations begin. Some of the bold claims don’t fully hold up in practice, while other capabilities are more impactful than they initially appear.

We took a closer look to separate genuine innovation from well-packaged marketing, and to understand what this means for developers, product teams, and businesses making decisions today.

Full breakdown in the article.

https://softwareplanetgroup.co.uk/claude-design-vs-google-stitch/

12/04/2026

A client approached us recently with a product entering a market that already has established alternatives. The obvious question was not just how to build it, but how to make it meaningfully different. Our suggestion was straightforward: invest in the user interface as a way to address real user pain points and create that differentiation.

Unfortunately, that path was not taken. It is a familiar pattern, and it usually leads to the same place. This experience prompted us to put together our perspective on the role of UI design in modern web services, and why it is often underestimated until it becomes a problem worth fixing.

https://softwareplanetgroup.co.uk/the-hidden-cost-of-ui/

01/04/2026

We often find that the most valuable moments in a project come from open and thoughtful conversations with our clients. These discussions help us validate that we are aligned on goals, expectations and, just as importantly, on the trade-offs that shape real delivery.

One such conversation recently focused on software quality. It raised a very practical question: what level of quality is actually needed to move forward without slowing the product down?

We have captured our perspective in this article and invite you to take a look.

https://softwareplanetgroup.co.uk/why-chasing-perfection-can-break-your-product/

28/03/2026

Humanoid robots are no longer a demo. They are becoming infrastructure

When Hyundai acquired Boston Dynamics, many treated it as just another corporate move. A big company buying a flashy robotics lab known for viral videos. Impressive, yes. Commercially meaningful, not quite.

That assumption is now breaking.

The new generation of Atlas is fundamentally different. Not because it dances better or jumps higher, but because it is clearly designed for real industrial use. This is where things get serious.

What stands out is a deceptively simple shift. Atlas is now effectively bidirectional. There is no front or back. Both sides are functional. In a factory environment, that detail changes everything. No need to turn, no wasted motion, no friction in tight production spaces. It moves like a system component, not a machine that needs accommodation.

And that leads to the second, more important point. It is humanoid by design, but not for aesthetics. It fits into existing production lines without forcing companies to rebuild their infrastructure. It can step into a human workspace and operate within it.

That combination creates an unusual leverage. Backward compatibility with existing processes, while opening the door to entirely new ones. It is not just optimisation. It is expansion.

For years, Boston Dynamics looked like a pure R&D story. Brilliant engineering, unclear business model. Hyundai changes the equation. This is a company that runs massive manufacturing operations. They are not investing in robotics for spectacle. They are integrating it into production.

Which means we are likely looking at a shift, not an experiment.

There has been a lot of discussion about AI replacing knowledge workers. Developers, designers, writers. That transition is already visible. But physical labour has been treated as something more resistant. Harder to automate. Too complex, too expensive.

Those constraints are starting to fall at the same time.

If that trend continues, the next wave will not come from software alone. It will come from the combination of AI and embodied systems operating in the physical world.

Factories and warehouses will be first. And the impact there will be far more visible.

The key question is no longer whether this will happen. It is how quickly organisations adapt to it, and whether they treat it as incremental automation or a structural redesign of how work gets done.

Curious to hear how others see this playing out in real production environments.

(6 Jan 2026) FOR CLEAN VERSION SEE STORY NUMBER: 4628217++AUDIO AS INCOMING++ASSOCIATED PRESSLas Vegas, US - 5 January 20261. Various of humanoid robot on st...

24/03/2026

Why software teams keep getting bigger, yet delivery feels slower

Something does not quite add up. Teams are more specialised than ever. Processes are more structured. Budgets keep growing. Yet delivery often feels slower, more fragile, and harder to control.

At some point, it is worth asking a different question. What if the problem is not in the tools, the frameworks, or even the people, but in how the work itself is structured?

This piece looks at software development from a slightly uncomfortable angle. It questions some common assumptions and offers an alternative that is simpler, but not necessarily easier.

If your team feels busy but the results do not match the effort, this might be worth your time. Have a read and see where it lands for you.

https://softwareplanetgroup.co.uk/why-generalists-win-in-software-development/

21/03/2026

Let’s look at an antipattern that shows up in real businesses all the time: task setting through fragmented messages.

On the surface, it feels efficient - a quick message, a short instruction, move on. In reality, it creates gaps. There is no immediate confirmation of understanding, no space for clarification, and no guarantee the task is interpreted as intended. Priority gets diluted, context is lost, and defects appear later when it’s already expensive to fix them.

This approach turns task setting into a one-way broadcast instead of a two-way alignment.

A simple shift solves most of this.

Use real conversation.

Whether it’s a quick call or a face-to-face discussion, real communication creates a feedback loop. You get immediate confirmation, questions surface early, and both sides align before ex*****on begins. Tone conveys importance and urgency without needing extra explanation. The task becomes clear, prioritised, and harder to ignore.

In other words, replace passive messaging with active communication - and you’ll reduce defects while increasing speed and ownership.

13/03/2026

How should an IT system behave - as a supervisor or as an assistant?

Many digital services today are designed like strict gatekeepers. If you try to register with a password that does not meet a long list of requirements, the system simply refuses to proceed. It blocks you until you comply.

But is this always the right approach?

Imagine you are creating an account in a simple weather application. Does the system really know how important this account is to you? For some users it may be critical. For others it may be completely disposable. Yet the system often assumes the role of an authority that knows better and forces everyone into the same behaviour.

There is another philosophy: systems that guide rather than police.

Instead of blocking the user, the system could simply explain the risk: “This password is relatively weak and may be easier to compromise.” The user stays informed, but the final decision remains theirs.

Good technology should help people make better choices, not punish them for imperfect ones. In many cases, respectful guidance creates a far better experience than rigid control.

The real question is simple:
Should digital systems enforce behaviour, or should they empower users to decide?

Curious to hear how others think about this.

06/03/2026

At first glance, modern LLMs appear to have taken over a large portion of a software developer’s work. They generate functions, suggest architectural patterns, write tests and even refactor code.

It would seem logical that this should dramatically reduce the cost of custom software development. If AI can produce code, why would companies still need the same level of engineering effort?

A deeper explanation of this can be found in the full article:

https://softwareplanetgroup.co.uk/why-llms-havent-reduced-the-cost/