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Extending Your Development Team

Rethinking AI Developer Expectations: What Startups Need to Know

By Tekkon teamPosted on Posted in Developers

As AI tools become more accessible and powerful, expectations for developers are shifting – sometimes in useful ways, and sometimes in ways that distract from what actually matters.

I recently ran a survey on LinkedIn and Facebook to gather community insights to better understand what founders and tech leads expect from modern devs in the age of AI.

The TL;DR? AI is changing how developers work – but not what makes them great.

Let’s Talk Titles

There’s a growing trend of startups listing “AI Engineer” roles that don’t actually require deep AI expertise. Often, these roles involve standard development with a sprinkle of LLM integration. And while the ambition is good, the mislabeling can signal to developers (and investors) that the company may be chasing buzzwords rather than building substance.

Smart hiring leaders are starting to course-correct: relabeling positions to reflect core skills (like “Software Engineer” or “Full-Stack Developer”) while keeping AI competency as a desirable add-on. This grounds hiring decisions in capability and culture fit – not just the latest hype cycle.

What Startups Are Doing vs. What They Should Be Doing

Our survey surfaced a clear pattern: many startups are dabbling with AI – integrating LLMs, automating pieces of workflow, or experimenting with open-source models. However, the real value seems to come not from novelty, but from identifying meaningful use cases.

Startups that succeed in applying AI:

  • Solve real problems (e.g. workflow automation, internal tooling, customer support augmentation).

  • Integrate AI as part of broader systems, not as the system itself.

  • Stay lean, test fast, and refine features based on actual user needs.

The caution? Don’t build AI features just because they’re trending. Build them because they move your product forward.

AI as an Accelerator, Not a Substitute

Another insight was around how devs use AI tools day-to-day. Many now rely on LLMs for tasks like debugging, boilerplate generation, or quick research. And it works – one respondent shared how they solved a multi-hour issue in minutes with the help of ChatGPT.

But while AI accelerates progress, it doesn’t replace good engineering habits. Developers still need to understand system design, architecture, and problem-solving. AI is a powerful assistant – not a free pass to skip learning the fundamentals.

Key Capabilities in Today’s Dev Landscape

So what should you expect from a great developer in 2025? Based on what we heard from the community and what we see at Tekkon, here’s the shortlist:

  • Strong core engineering ability in your stack (frontend, backend, or full-stack).

  • Fluency in cloud platforms and modern dev workflows (CI/CD, API integration, automation).

  • Comfort using AI tools like OpenAI APIs, Hugging Face, or even building internal prompts/scripts.

  • Pragmatism – knowing when to use AI and when not to.

  • Team fit and communication – especially in remote or async setups.

Final Word: Hire for Curiosity and Craft

At Tekkon, we work with startups who move fast. They don’t just want someone who knows the latest tech—they want someone who can help ship products, solve real problems, and adapt as the landscape changes.

If you’re hiring and looking for that rare combo of practical skills + AI fluency + startup mindset, we’d love to help.

Let’s find your next Tekkie – so please connect with us anytime to find out more or find us on LinkedIn.

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