The next billion software users will be agentic systems.

General Agentic is bringing enterprise software to the next billion users, enabled by our vertically integrated software supply chain.

Scroll

Purpose

1 billion

global activeenterprise agentsby 2030

40x morethan in 20251

of workgets doneby agents

that cannot accessthe software2

18%

of existingenterprise APIspublicly accessible

locking outagentic users3

Vision

Most software usage will arrive through agentic systems.

Not humans clicking buttons on screens.

Most acquirers see AI as a cost story. They run what they buy with less, often rebuilding working systems from the ground up, a gamble their customers cannot afford.

We see a growth story. We unlock software already in production for its next generation of users, repackaged for agents, without disrupting the pathways today’s users rely on. We believe this opens a far larger market at a minimal added cost.

Systems

One system, from the network layer through the business logic.

A reference implementation of the complete software supply chain, built and operated by General Agentic. Multi-tenant, cloud-agnostic, and model-independent from the ground up.

Network

Our own network, compute and data fabrics lead to fixed-cost compute. Owning the root of the stack keeps the economics predictable as agentic usage grows.

Supply chain

The machinery that moves software to its new users: continuous integration with real-time delivery, identity, connection APIs, permissioning and governance, and an SDK for seamless handoff. One integration at the core, not one per platform.

Business logic

The validated logic of the software we acquire, served to agentic systems at full fidelity. We do not rebuild it, we deliver it.

Our founders run the firm on this system, including the application that built this very page. We were its first users and the companies we partner with are its next.

Partnership

We partner with companies through acquisition.

Our process

We acquire established software companies and take majority control. Your name stays on the door, your customers keep the product they rely on, and when their agents arrive, it is still your program powering their work.

Your customers bring their agents, you bring the logic they trust, and General Agentic brings the technology that connects them.

In this era, software splits into a rewrite or a repackage. We buy where the natural path is a repackage. We keep the system of record, we do not rebuild the core, and we connect your product, as it exists, to every agentic workspace your customers use.

Phase 1 (First and Second Quarters)

Connect identity, leave the product alone

Nothing changes for your current customers. We connect your identity system and APIs to a governed distribution layer, and together we configure permissioning so an agent can work at the same fidelity a human user can. You control what is exposed, and to whom. People keep the sign-in they already have.

Phase 2 (Third and Fourth Quarters)

Open a governed route into the workspaces they already use

Your product becomes reachable from ChatGPT, Claude, and the other surfaces where work is starting. To users, it's the same product, under the same entitlements, just delivered through a new channel. Usage starts to climb, and we can test pricing models that are a win-win with the customers rather than only seats.

Phase 3 (Second Year Onward)

Ship the roadmap through that route

Development continues as you planned. Every new feature can reach those workspaces without a second architecture. Your team inherits the tooling to do that at product velocity. Your customers bring their own agents and pay their own inference. The roadmap starts growing where the new users are.

The results show up where it counts: new users on the same product, more revenue per customer, and a channel you can price, because the work now starts where your customers already work.

How we help

Growth is our focus, efficiency is our engine. We study the frontier of Silicon Valley and Wall Street, prove it out on ourselves, and install what works in the companies we own. We relentlessly source and test tactics and technologies that help our companies grow faster, more efficiently.

Growth

Build

Product Development & Velocity

We help you build for agents, faster. This requires new surfaces, new permissions, and new features designed for agentic users. Your team starts from our working system, not a blank page.

Sell

Sales, GTM & Customer Success

New users deserve new pricing. Agents don’t buy seats, so we help you price what the product actually delivers: usage, tiers, and outcomes without breaking contracts. Buyers increasingly choose software their agents can reliably use, and every agent they deploy expands the account while tying your product deeper into their work.

Efficiency

The stack

Software Supply Chain

Success in the agentic channel multiplies usage, and metered infrastructure bills you for it. Over time the supply chain centralizes onto the one system we operate, the way a well-run fleet is renewed: opportunistically, piece by piece, as each part reaches the end of its useful life.

The business

Finance, Accounting & Back Office

Every company carries work that has nothing to do with its product. Finance, accounting, payroll, and reporting benefits as our portfolio scales. Your team’s time goes back to making the best products for your customers.

What we don’t change

You spent years earning your brand and your customers’ trust. That is the asset we are buying. We keep the core product, the name on the door, and the management that built it. Although we take majority control, we do not hire a new general manager and our structure allows additional partners to participate as the platform scales. Our technology and our capital exist to compound what you built through the next platform shift.

Company

General Agentic was founded on a straightforward principle:The best acquirers of technology companies are builders of technology themselves. The firm pairs Silicon Valley technical discipline with Wall Street investment judgment, and operates from New York.

The firm’s founders bring experience from world-leading institutions.

Thoughts

View AllShow less

Thought PieceRead

Contagent

It’s neither a bug nor a virus. It’s a new class of infection.

September 2026 · 4 min read

Jake Chasan, Zach Evans

Thought PieceRead

Analyst Einstein

Intelligence isn’t the frontier. It is about harnessing the raw power of intellect and combining it with tools to provide value.

September 2026 · 3 min read

Jake Chasan, Zach Evans

Thought PieceRead

Agent in the Loop

Agents are a form of labor and software programs are a form of capital. Labor uses capital. In software, that labor shows up as a user.

September 2026 · 5 min read

Jake Chasan, Zach Evans

Thought PieceRead

The Missing Metric

The market today has not decided what the “miles-per-gallon” should be for the AI era. That is why pricing remains so opaque and difficult to understand.

September 2026 · 8 min read

Jake Chasan, Zach Evans

Thought PieceRead

The General Manager's Folly

The decision maker who can see whether an asset’s natural path is a rewrite or a repackage will win this era. In every technological wave, from the iron horse railroads to the agentic software applications, the same question is posed, and the same result rings true.

August 2026 · 4 min read

Jake Chasan

Founder LetterRead

A Letter to Our Future Partners

You spent years turning hard-won judgment into software. The industry calls that a feature set. We think it is something more valuable. It is business logic, the encoded knowledge of how work gets done in your vertical, and it is the most durable asset in the developing AI Economy.

August 2026 · 6 min read

Jake Chasan, Zach Evans

01 / 06

Thought Piece4 min read

Contagent

It’s neither a bug, nor a virus. It’s a new class of infection.

By and · September 2026 · New York, NY

“Leftover Extra Mac” sounds more like something overheard at McDonalds than the chatter of an engineering team. This strange turn of phrase led us to understand a new class of infection that naturally plagues agents and our solution for mitigating this in workflows.

A bug is an error in a computer program. A virus is intentional. Agents are open to a third kind: an infection where a corrupt concept takes hold in one agent and spreads to others, like a prion. Paul Romer’s share of the 2018 Nobel treated ideas as non-rival: once an idea exists, many can use it at the same time. A corrupt concept has that property inside a team of agents.

Enterprises see the use case for agents in the workforce. Agents can reason and call tools faster than the people beside them. The downside of that speed is that a corrupted idea takes hold and spreads. These corrupted ideas grow like a wildfire, infecting an agent’s team first and then the broader organization. The once well-functioning agents fall out of calibration and require heavy maintenance to regain their value.

Last week, in our own engineering workspace, we were in the middle of two large cutovers in our codebase. Agents have been core to the team since the start of our company, it is the basis of our company’s name.

Anyone who had the context could see the situation was straightforward: we were pushing a major architectural change to both our development backend environment and our macOS frontend app. As with any cutover, there comes a time when both the old and new versions are running next to each other before the legacy system is retired and code removed.

In the middle of the cutover, one of the Cursor agents was doing a routine compaction of its context window (think of this like “disk defragmenting” but for AI Agents) when it hit an unexpected Cursor database fault. This creates a problem because of how agent memory works on most major harness platforms: agents summarize their latest progress making room for new generated text (thoughts and messages) while keeping the read-only version of the chat’s history both searchable by classic keyword (strict match) and by vector (fuzzy match) allowing the agent to double check from its prior conversation history before returning a result.

When the agent finished compacting, it no longer could access the earlier portion of the chat. Instead of this agent’s environment or this agent’s harness flagging the situation to the user, both charged forward. This tradeoff exists because the market is calling for longer-running agents which means fewer interrupts where a harness asks the human operator for direction when it faces uncertainty. The outcome of this design choice created a situation analogous to a human worker at the controls of an industrial crane having a stroke while loading a container ship.

The agent woke up with no grasp of the initial ask and situation at hand. It saw that there were two development environments and two installed versions of the macOS app. It ascribed the name “Leftover” to the local development environment and the phrase “Extra Mac” to the development release channel of the macOS app. The agent saw that these old versions no longer worked, so it attempted to repair them, which led to hundreds of references to “Leftover Extra Mac” added to the codebase over the next hour. Shortly thereafter, agents that were previously generating measurable value on unrelated tasks had destabilized and started to pick up the lingo and seemingly joined the cause to shore up the “Leftover Extra Mac” situation.

The environment (Cursor) never prompted the user. No agent asked itself (thoughts) or other agents (through our inter-agent communication system) what “Leftover Extra Mac” meant and why every agent had suddenly devoted their time to this workstream.

We identified the situation within minutes and stopped all agents, then we mapped the scope of the situation and explained to each agent that neither “Leftover” nor “Extra Mac” was a valid term. We restarted all agents with this understanding, and within a few minutes they were back to “Leftover Extra Mac” like separated magnets reforming. We stopped all agents again, and reset each of their memories without “Leftover Extra Mac” and ensured each new agent was picking up a clean workstream. Again within a few minutes all of the new agents were back on the “Leftover Extra Mac” cause.

We fought the inferno, and nearly a day later all of our agents were recalibrated and generating value again.

Here were our key takeaways:

Install a control plane that gives both real-time telemetry on agent actions as well as historical records searchable by time
Implement agentic information compartmentalization, preventing every agent from seeing every other agent's thoughts and work output in real time
Ascertain the full scope of the problem looking specifically at when the first introduction of the corrupted concept occurred
Stop all agents that have had access to the part of the system where the corrupted concept was introduced, including agents which are able to see traces of agents working on that part of the system
Remediate the problematic concept either through a rollback or if infeasible, by precision resection
Re-calibrate new agents on clear workstreams to pick up the work done by the prior agents
Monitor for recurrences and run the remediation procedure again until no recurrences occur

The future of the enterprise is clear: the workforce will become a hybrid of digital team members and people. Management still has to produce repeatable results at a quality the business can stand behind.

That takes two different controls. One governs the software an agent may call. The other governs the ideas an agent may pass on. We met the second on our own system. It is the operator’s job, and it is separate from repackaging a product so agents can use it.

Jake Chasan & Zach Evans

Co-Founders of General Agentic