# Open Agent Stacks Gain Favor as Enterprise Adoption Rises and Software Reprices *By VC Tech Radar • April 12, 2026* Investor sentiment is coalescing around open, provider-agnostic agent infrastructure while new teams attack memory, security, and browser automation. The broader backdrop: agents are moving into production quickly, but public software is being repriced around AI substitution risk. ## 1) Funding & Deals - **Baobab Ventures is a useful read on current seed taste.** Carles Rayner said his solo GP fund backed Revolut and ElevenLabs early, and that he looks for scrappy founders and non-obvious companies that other VCs pass on. [^1] - **Cogveo is pursuing early-access financing while still pre-scale.** The solo founder is building the product while working full-time and is using Kickstarter for early access funding; the product automates recurring AI work on uploaded files, runs saved "skills" autonomously, and generates deliverables such as PPTX, DOCX, XLSX, and PDF inside a Docker sandbox. [^2] - **SeqPU is a commercialization infrastructure play for open models.** Its pitch is to abstract Docker, deployment, billing, and scaling so notebook experiments can ship as Telegram bots, UI sites, or APIs with per-second compute billing and pay-per-use markup, explicitly aimed at monetizing open-source models without per-token API costs. [^3] ## 2) Emerging Teams - **Subaiya** is building a cloud security proxy for AI agents rather than another sandbox. It adds prompt-injection detection, sensitive-file protection, 20 permission categories with On/Ask/Off controls, and a real-time activity feed with emergency stop; feedback in-thread framed prompt injection and sensitive-file protection as the main blockers to shipping agent tools. Current integrations include OpenClaw, Anthropic, and OpenAI, and tool-call inspection is regex-based rather than LLM-mediated. [^4][^5][^4][^6] - **Thoth** is an open-source agent harness built on LangGraph and promoted by Harrison Chase. The core wedge is a personal knowledge graph with 67 typed directional relations, graph-enhanced recall via FAISS + NetworkX, Obsidian export, a nightly "Dream Cycle" for graph refinement, and map-reduce document extraction with provenance. [^7][^8] - **Iranti** is a self-hosted MCP memory layer for Claude Code and Codex that lets tools write facts centrally and inject relevant context into future sessions, so the user no longer has to re-explain project state across tools. It is AGPL-3.0, fully self-hosted, and currently requires Postgres. [^9] - **SearchAgentSky** is a browser-native agent that opens real sites, follows links, and writes answers while users watch the browser and a raw "Agent View" terminal. It runs entirely in-browser with a QuickJS-to-WASM sandbox, persists sessions across refreshes, and early feedback highlighted the live browsing view as a trust/debugging advantage over black-box RAG. [^10][^11] ## 3) AI & Tech Breakthroughs - **Portable memory is separating from the harness.** Garry Tan's "thin harness, fat skills" thesis argues memory and skills should live as markdown in a git repo rather than inside the runtime. He said his open source is used by tens of thousands of agentic engineers per day after three months, and GBrain packages a Claw/Hermes schema, skillpack, RAG memory system, and direct voice access via WebRTC + Twilio. [^12][^13][^14][^15][^16] > "If your memory dies when your harness dies, you built the harness too thick." [^13] - **The agentic web stack is becoming more concrete.** MIT Open Agentic Web discussions emphasized identity, attestation, reputation, and registry layers as the missing DNS-equivalent for agents. The discussion also focused on persistent agents that discover, negotiate, and transact across networks, with protocol design, coordination, and provenance framed as the hard problems. [^17] - **KellyBench is a useful reality check on long-horizon reasoning.** General Reasoning reported that models from Google, OpenAI, and Anthropic lost money betting on Premier League matches over a full season, highlighting a gap between strong performance on tasks like software writing and weaker long-term real-world analysis. [^18] ## 4) Market Signals - **Enterprise agent adoption is still early, but the operational footprint is already large.** Databricks says only 19% of organizations have deployed AI agents, yet agents already create 97% of database branches and 80% of databases on Neon. Multi-agent systems grew 327% in four months, tech companies build nearly 4x more than other industries, and 78% of companies now run two or more LLM families. Governance and evaluation are strongly associated with production success, at 12x and 6x more projects respectively, while Supervisor Agent reached 37% of Agent Bricks usage within four months. [^19] - **Investor sentiment is hardening against proprietary agent stacks.** Garry Tan argues startups building critical operations on Claude Managed Agents or other proprietary harnesses are not investable because the IP sits on an unstable foundation; his preferred alternative is an open, provider-agnostic framework with model diversity, local or fine-tuned models, and private/E2EE options. Imbue is making the same strategic bet around an open agent ecosystem and user control over algorithms and agents. [^20][^21][^22][^23] - **Public software is being repriced around AI substitution risk.** SaaStr's index of top public software companies is down 50.5% over six months, and forward application-software P/E has fallen from 84x in 2021 to 22.7x. The reported drivers are budget displacement toward AI infrastructure and fear that agents erode seat-based models; Harry Stebbings added an anecdote of a $10B public company replacing $1.2M per year of software with a custom build in three weeks, while Martin Casado argues that if cheap capital slows, value will flood downstream. [^24][^25][^26] - **AI GTM is shifting from outbound to leverage inside support and experimentation loops.** In a 20VC interview, ElevenLabs said outbound response rates have fallen below 0.01%, customer support is its fastest-growing revenue product, and internal AI agents for inbound SDR, proposals, and customer success are being used to target 50% productivity gains. The same conversation framed GTM as a portfolio problem—testing many markets and channels in parallel—and noted that customer-support AI is already crowded, with 16 providers having raised more than $75M in the last 18 months. [^1] - **Open-model supply is likely to bifurcate.** Interconnects argues that near-frontier open models will eventually need a consortium as training costs move from millions to billions, while most companies will be more willing to release smaller, fine-tunable models than fully open frontier systems. [^27] ## 5) Worth Your Time - **[Databricks State of AI Agents 2026](https://www.databricks.com/sites/default/files/2026-01/State-of-AI-Agents-2026-Final.pdf?utm_source=tldrfounders)** — useful quantitative benchmark for deployment rates, multi-model behavior, governance, and the rapid rise of supervisor agents. [^19] - **[The inevitable need for an open model consortium](https://www.interconnects.ai/p/the-inevitable-need-for-an-open-model)** — useful framing on why open-model supply may consolidate into consortia while smaller fine-tunable models proliferate. [^27] - **[MIT Open Agentic Web conference post](https://www.reddit.com/r/artificial/comments/1siypay/)** — concise field notes on identity, attestation, coordination, provenance, and why expert augmentation still appears more robust than full replacement. [^17] - **[Thoth](https://github.com/siddsachar/Thoth)** — a concrete reference implementation for knowledge-graph memory, Obsidian export, and provenance-preserving document extraction in agent systems. [^8] - **[20VC / ElevenLabs on modern AI GTM](https://www.youtube.com/watch?v=9ereyZiA99o)** — useful for the combination of AI-led productivity, customer-support monetization, and the claim that outbound is now effectively broken at scale. [^1] [![ElevenLabs: Building an AI Sales Machine & Why We Set a 20x Sales Quota](https://img.youtube.com/vi/9ereyZiA99o/hqdefault.jpg)](https://youtube.com/watch?v=9ereyZiA99o&t=234) *ElevenLabs: Building an AI Sales Machine & Why We Set a 20x Sales Quota (3:54)* --- ### Sources [^1]: [ElevenLabs: Building an AI Sales Machine & Why We Set a 20x Sales Quota](https://www.youtube.com/watch?v=9ereyZiA99o) [^2]: [r/SideProject post by u/thrinz2](https://www.reddit.com/r/SideProject/comments/1sj3kpb/) [^3]: [r/SideProject post by u/Impressive-Law2516](https://www.reddit.com/r/SideProject/comments/1siobai/) [^4]: [r/SideProject post by u/Subaiya](https://www.reddit.com/r/SideProject/comments/1sih71e/) [^5]: [r/SideProject comment by u/farhadnawab](https://www.reddit.com/r/SideProject/comments/1sih71e/comment/ofk0k6i/) [^6]: [r/SideProject comment by u/Subaiya](https://www.reddit.com/r/SideProject/comments/1sih71e/comment/ofk26jp/) [^7]: [𝕏 post by @hwchase17](https://x.com/hwchase17/status/2043007430833918434) [^8]: [𝕏 post by @SydSachar](https://x.com/SydSachar/status/2043003879223124068) [^9]: [r/SideProject post by u/Adventurous-Swim9405](https://www.reddit.com/r/SideProject/comments/1siv8me/) [^10]: [r/SideProject post by u/VolumeTechnician](https://www.reddit.com/r/SideProject/comments/1sj3xuo/) [^11]: [r/SideProject comment by u/Otherwise_Wave9374](https://www.reddit.com/r/SideProject/comments/1sj3xuo/comment/ofoz5c0/) [^12]: [𝕏 post by @garrytan](https://x.com/garrytan/status/2043198783006355747) [^13]: [𝕏 post by @garrytan](https://x.com/garrytan/status/2043198780800197025) [^14]: [𝕏 post by @garrytan](https://x.com/garrytan/status/2042939656438976854) [^15]: [𝕏 post by @garrytan](https://x.com/garrytan/status/2043069983434084464) [^16]: [𝕏 post by @garrytan](https://x.com/garrytan/status/2043070257485746201) [^17]: [r/artificial post by u/jradoff](https://www.reddit.com/r/artificial/comments/1siypay/) [^18]: [𝕏 post by @nathanbenaich](https://x.com/nathanbenaich/status/2042577919822750016) [^19]: [Databricks: Only 19% of Organizations Have Deployed AI Agents. But They’re Already Creating 97% of Databases.](https://www.saastr.com/databricks-only-19-of-organizations-have-deployed-ai-agents-but-theyre-already-creating-97-of-databases) [^20]: [𝕏 post by @jtlin](https://x.com/jtlin/status/2043049539872133436) [^21]: [𝕏 post by @garrytan](https://x.com/garrytan/status/2043060980918423823) [^22]: [𝕏 post by @imbue_ai](https://x.com/imbue_ai/status/2043004125559034138) [^23]: [𝕏 post by @kanjun](https://x.com/kanjun/status/2043047995487478254) [^24]: [The Leading Public Software Companies Are Now Down -50% in the Last 6 Months](https://www.saastr.com/the-leading-public-software-companies-are-now-down-50-in-the-last-6-months) [^25]: [𝕏 post by @HarryStebbings](https://x.com/HarryStebbings/status/2042975028073951711) [^26]: [𝕏 post by @martin_casado](https://x.com/martin_casado/status/2043036154333925871) [^27]: [The inevitable need for an open model consortium](https://www.interconnects.ai/p/the-inevitable-need-for-an-open-model)