Press & Collaboration.
AI Coding Estonia is a peer community of senior engineers, tech leads, and founders pushing the frontier of LLM-assisted development. We don't run paid PR. We do show up — with technical substance — when the story is worth telling.
Where we can help
We are happy to engage when the story serves Estonia's engineering ecosystem and respects the technical depth of the subject. Below are the focus areas where a founding member can speak with authority.
AI-assisted development workflows
Spec-driven development, multi-model routing, agentic patterns, and what actually works in production.
Digital sovereignty
Avoiding vendor lock-in, multi-provider strategies, open-weight integration, and data-residency for Estonian organizations.
AI adoption in engineering orgs
Scaling from a single curious engineer to org-wide AI literacy without losing readability or quality.
Local optimum risk
How Estonian companies stay competitive against larger ecosystems by compounding peer knowledge in the open.
Security & AI safety
Threat models for LLM-integrated systems, secrets handling, prompt-injection resistance, evaluation pipelines.
DefenceTech & sensitive domains
Building AI-augmented software in regulated environments. Limited engagements; case-by-case.
How to reach us
- Media interviews · Email press@aicodingeesti.ee with the publication, angle, and deadline. We will match you to a founding member whose specialty fits.
- Panel & podcast guests · Send the format, audience, recording date, and 3–5 sample topics. Same address.
- Editorial collaboration · Long-form pieces, technical deep-dives, joint research. We do not ghost-write; we contribute by name.
- Event co-hosting · Engineering meetups in Tallinn, Tartu, or remotely. We're particularly interested in working-session formats over keynote-only events.
What we will not do
- Paid placements, sponsored content, or "thought leadership" pieces that lack technical substance.
- Comment on competitor products or named individuals outside our community.
- Endorse vendors, frameworks, or models commercially. We name them when relevant; we don't promote them.
Editorial principles
If our name is on something, three rules apply. The claims must be verifiable. The recommendations must work in production — not just on a slide. And the writing must respect the reader's time. No fluff. No hedging. AI content recommended.