Executive Summary

Developers and engineering teams who use multiple coding assistants (IDE plugins, web UIs, CLI agents, and PR bots) face fragmented conversational history that makes it hard to reuse prompts, reproduce debugging sessions, and retain rationale behind decisions—this is a recurring pain for an estimated 2.6M heavy coding-agent users. That lost context translates into wasted engineering hours and duplicated effort across projects and tools. Build a privacy-first platform that ingests and indexes agent conversations into a vector database with metadata, session-level summaries, deduplication, and fast semantic search exposed via IDE plugins and an API. Enable retrieval-augmented agent workflows so new agents can query past sessions, and include enterprise features like fine-grained access controls, retention policies, and provenance export. The market is timely and sizable: roughly $2.34B in addressable revenue (2.6M users × $900 ACV) as multi-agent adoption grows and embedding/vector DB costs fall, making it affordable for small teams to index large corpora. Agent-to-agent workflows and programmable CLIs create an immediate need for history-aware tooling that improves developer velocity. You can stand out by prioritizing developer UX and deep integrations (IDE/CI/agent platforms), offering strong provenance/privacy controls, and converting chat logs into actionable, summarized knowledge for downstream agents — but expect significant integration work and the need to build trust around data governance before capturing enterprise customers.

Market Opportunity

Find and reuse developer agent conversations across tools targets a $2.34B = 2.6M heavy coding-agent users × $900 ACV total addressable market with medium saturation and a year-over-year growth rate of 15% CAGR — estimated growth driven by developer tool adoption and AI assistant usage (based on Stack Overflow developer trends and AI tooling market signals).

Key trends driving demand: Multi-agent adoption — developers increasingly use multiple coding assistants, creating fragmented conversational traces that need unified search.; Cheap embeddings and vector DBs — lower storage and retrieval costs make indexing large session corpora affordable for small teams.; Agent-to-agent workflows — the rise of CLI and programmable agents creates demand for history-aware agents that can query past sessions.; Personal knowledge demand among developers — prosumers and small teams want instant recall of prior prompts and generated code to avoid duplicated effort..

Key competitors include Sourcegraph, Glean, Mem (and similar personal knowledge tools).

Sign in to access

Find and reuse developer agent conversations across tools

Executive Summary

Market Validation

Market Opportunity

More in Developer Tools

Manage dozens of websites with centralized automation and governance

Reduce latency & cost with AI-driven backend optimization for mobile games

Missed sales from phone leads fixed by an API phone system that captures and qualifies

AI coding tools lose context, provide persistent cross-tool memory

Open-ended scientific tasks lack rigorous, domain-expert benchmarks

Fix fragile delivery-app checkout flows with AI-driven test & observability