A quick look at the financials of AI products.
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💬 Topics:
- Death of Solo Coding;
- Rise of Dev Rituals
- Spec Over Code;
- AI Orchestration Chaos;
- Engineering Still Matters;

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Spec-driven development is examined with skepticism: the methodology requires frontloading all thinking into a machine-readable spec before writing code, which contradicts how real-world complexity is discovered during implementation. Tools like GitHub Spec Kit and BMAD (AI agent orchestration via markdown files) are pushing this approach. While AI coding gives an 80% speed boost for simple apps, studies including the 2026 DORA AI report show a U-shaped productivity curve where real-world complexity causes productivity to drop below baseline. Over-reliance on AI also correlates with more software instability and weakened developer skills. The conclusion: the last 20% of real engineering — edge cases, debugging, abstraction — remains irreducibly human.

Does spec-driven development really work?

Works in spending alot of tokens, my enterprise forcing Kiro, i only used it spec mode once, in a perfect world, you would MCP the Jira User stories into Specs and create a PR and merge to main, all using agents, but for complex projects, its a 30% chance of expected output.

I hate BDD, and have seen it fail miserably in many organisations. This spec driven development is bound to fail too

only if person leading the team had a good idea of what he/she is doing and explaining the same to the team in the correct manner by following with example then only it will work.
It’s not like shinny thing which can you learn by googling or with AI, it will be one of least effective method