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title: Reviews of DevAI Conference 2026 From a Speaker’s Eye
description: A developer recaps DevAI 2026 in Warsaw, a conference with 50 presentations across 4 tracks covering AI topics. One team transformed a Java recruitment system...
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# Reviews of DevAI Conference 2026 From a Speaker’s Eye

**[We Are .NET](https://daily.dev/sources/wearedotnet)** · 30 min read · 0 upvotes · 0 comments

## Summary

A developer recaps DevAI 2026 in Warsaw, a conference with 50 presentations across 4 tracks covering AI topics. One team transformed a Java recruitment system to .NET 10 + Blazor + PostgreSQL, reporting 19 working days to a functional platform and 10 weeks to production versus an estimated 7-9 months traditionally, and used spec-driven development. Another speaker described NER-RAG, which reports 330x cheaper document processing than LLM-based extraction in their illustrated scenario. A study of 806 GitHub projects using Cursor, presented by a speaker, reported a 41.6% increase in code complexity and a 30.3% increase in static analysis warnings over the longer term. A separate talk catalogued coding agent failure modes: one agent overestimated task time by up to 177x, a development environment had 268 stale Git branches on a single laptop, and sycophancy and tunnel vision were discussed.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://abp.io/community/posts/reviews-of-devai-conference-2026-from-a-speakers-eye-tmtqs75j>

## Questions this post answers

### How much faster was a .NET rewrite using spec-driven AI development compared to traditional development?

A 10+ year-old Java recruitment system was rewritten to .NET 10, Blazor and PostgreSQL in 19 working days to a functional platform and 10 weeks to production, versus an estimated 7 to 9 months with traditional development. The team followed a process of business problem to specification to plan to small tasks to code and tests, with human approval at every stage, and shipped 69 changes after adopting it.

_Teams weighing AI-assisted rewrites can track real-world results like this one on daily.dev._

### Does using Cursor to write code actually increase long-term code quality?

No. A study comparing 806 GitHub projects that adopted Cursor against 1,380 similar projects found code production increased 28.6% to 281% initially, but code complexity rose 41.6%, static analysis warnings rose 30.3%, and duplicate code density rose 7.03% over the longer term, with the initial productivity gains disappearing within 1 to 2 months.

_Developers deciding whether to lean on Cursor long-term can follow findings like this on daily.dev._

### Why do AI coding agents overestimate how long a task will take?

Coding agents like OpenCode, Codex, pi and Claude Code gave time estimates far higher than their actual execution time in one comparison: OpenCode (GPT-5.5) estimated 18 hours for a task that took 6.1 minutes, a 177x overestimate, while Claude Code overestimated by 12x. One explanation offered is that models generate estimates based on patterns from human development timelines rather than their own execution speed.

_Anyone relying on agent time estimates for planning can track agent-behavior findings like this on daily.dev._

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#architecture](https://daily.dev/tags/architecture), [#rag](https://daily.dev/tags/rag), [#conference](https://daily.dev/tags/conference), [#spec-driven-development](https://daily.dev/tags/spec-driven-development)

[View this post on daily.dev](https://daily.dev/posts/reviews-of-devai-conference-2026-from-a-speaker-s-eye-wdpxm1ly3)

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