3 AImigo
Three co-hosts compare AI-assisted engineering practice, large engineering-organisation management, and AI4SDLC architecture.
About the series
3 AImigo avoids a single supposedly correct picture: the co-hosts separate established practice, team-level systems, and strong experiments that have yet to survive production.
Across the first seven episodes, Alexander Polomodov, Evgeny Sergeev, and Aleksey Litvinov establish a baseline for AI in software development, examine constraints on end-to-end delivery, redesign hiring as an evaluation system, discuss how new engineers can enter the profession, and look for a sustainable way to learn amid constant AI changes. Monthly digests connect the news into one engineering picture: in August, cheaper AI and harder adoption; in September, agent harnesses turning into vendor products and control over agent work.
Hosts
All episodes
September 2026 AI Digest: Cheaper Generation, Costlier Verification
The September digest moves the conversation from the models themselves to the systems around them: OpenAI sells the Codex harness as the Agents API, providers push cloud agents and new plans, and agents gain traces, policies, and outcome metrics like production services.
How to Keep Up with AI Changes Without Draining Your Energy
Models, agents, and research arrive faster than anyone can evaluate them. Chasing every update takes time away from practice and independent thought.
A Junior Without Easy Tasks. How Do You Enter Tech in the AI Era?
Building a product is easier, but landing a first engineering job is harder: AI takes over the small tasks that once trained new engineers.
AI Hires AI. How Do We Redesign Tech Interviews?
AI now participates on both sides of hiring, so banning a tool cannot restore the old signal: résumés and familiar online stages increasingly fail to predict performance in the role.
August 2026 AI Digest: Cheaper AI, Harder Adoption
Six connected stories from August reveal the same shift: access to models is getting cheaper while building a working AI system is getting harder.
AI Writes More Code. Why Doesn't Delivery Speed Up?
AI can make an individual engineer write code much faster, yet a higher volume of changes does not by itself shorten end-to-end delivery of value to users.
Where AI Stands in Software Development
The first 3 AImigo conversation compares three practical lenses: AI4SDLC, AI-Assisted Engineering adoption, and management of a large engineering organisation.