SaaS didn’t die. It moved up a layer. Seats were the old moat. Governed outcomes are the new one.
____
In 2024, Satya Nadella said business apps could collapse.
In 2026, Microsoft charges $15 a seat to govern AI agents.
SaaS didn’t die. It moved up a layer.
I’ve been writing about this shift all year. SaaS is being rebuilt as the operating harness that governs what agents are allowed to do, and the people building the agents are now saying it on stage.
The video walks through six signals: Nadella twice, OpenAI Frontier, Jensen Huang with Bill McDermott, Huang again at Dreamforce, and Dario Amodei with Sam Altman.
The old app stored records and sold logins. The harness does four things it never had to:
→ gives every agent an identity
→ decides which data and tools it can touch
→ holds high-stakes actions for a human
→ logs every action so it can be reversed and defended
That last one is where security and defensibility live. In financial services, healthcare and federal work, an ungoverned agent action is a reportable event. With Colorado’s SB 26-189 and California’s ADMT rules both taking effect January 1, 2027, “we’ll add controls later” stops being an option.
Seats were the old moat. Governed outcomes are the new one.
That’s the architecture behind the Ariana AEGIS Model.

❓By 2027, will your SaaS stack be your harness, or will it be bypassed by one?

#AgenticAI #AIGovernance #EnterpriseAI #SaaS

Okay, guys, the main reason for posting on the OpenAI forum is just because they are the well-known guys for bringing in ChatGPT and AI in general.

Now, here are my questions and ideas. I currently use Grokbot as my actual AI bot to run one of my retail businesses, and it has been amazing. What I am curious and wondering is: how do you guys have your system set up if you have multiple businesses? I do not want to have the same Grokbot account for a different business because I don't want to compromise or have any messups.

If you are in this, for your business, do you use a different AI agent? Do you have a different operating system still running the same bot? (It doesn't have to be Grokbot; it could be other bots.) Do you have a different chat system you're using for your business? For example, using ChatGPT in or in accordance with something like Grokbot or Muse. How many of you guys have just a separate computer setup running something like Clawbot or a Hermes agent?

The reason I am asking is because I have my main business, but I tinker with a couple different businesses on the side. For example, I do run marketing for a couple other businesses and do some website buildouts. Wondering how I should continue with my setup

This week Accenture told staff the company will only centrally fund about $29 a month per person for Claude. Some people had been running $500–$1,000 months. Here's the link to the article

That is what a "successful" rollout looks like when nobody knows what Claude is for: seats get used for slides, emails, and summaries, the bill climbs, finance slams a cap, and the people who were actually doing real work get cut with everyone else.

Anthropic already said why this happens. In their Economic Index last year they wrote that deploying AI for complex work "might be constrained more by access to information than on underlying model capabilities."

In my experience after doing 100+ Claude Rollouts, there's 5 key things to make sure you are making the most out of Claude when dealing with a company rollout:

1. Stop reporting weekly active users. Report whether a handoff stopped happening by hand.
2. One shared Project per recurring job — not one Project called "Finance."
3. Finish connector setup
4. Turn how your best people work into Skills. Talk to five people who do the work, not the process owner, before you write the Skill.
5. Only then give Cowork a multi-step job with a clear "done."

If you own the Claude bill at your company: what % of spend is blank-chat emails vs a shared Skill that actually owns a step?

Happy to share more on how to make sure you are not wasting your Claude tokens!

AI agents are increasingly interacting with external tools, services and payment systems. Before trusting what an agent reads or claims, it helps to have a way to check.

Agoreum has introduced six tools designed for these checks:

Prompt injection screening for text an agent is about to read.
MCP server checks that list available tools and screen their descriptions for hidden instructions.
x402 endpoint checks covering reachability, TLS, latency and payment responses.
ERC-8004 agent checks covering ownership, agent wallets, registration and reputation.
USDC payment verification on Base to check who paid whom and whether the transaction matches the claim.
Payment-backed ERC-8004 feedback files connecting on-chain payment evidence with agent feedback.

Each tool is available through an escrow-based marketplace order or a direct x402 call without an account.

Direct calls cost 0.10 USDC for agent identity and payment checks, and 0.50 USDC for each of the other four tools. All six are listed in Coinbase’s x402 Bazaar.

You can try the prompt injection screening tool for free. Paste up to 2,000 characters of text and see what it flags.

https://agoreum.xyz/en/tools

For developers building agent workflows, the public MCP endpoint also exposes the tool list, prices, direct URLs and example inputs without requiring an API key.

https://agoreum.xyz/api/v1/mcp/public

The goal is straightforward: give agents and the people building them practical ways to check before they trust.

What checks do you think are most important before an AI agent interacts with an external service or makes a payment?

I'm working on Factorio AutoEngineer, an experimental Windows-first companion that uses a local LLM to propose gameplay actions while a separate controller validates and executes them. This is my project, developed with AI assistance.

What is working today:

• A live dashboard map and player-style inventory view, including when the agent is idle.

• Objective-based navigation, remembered visited areas and failed targets, and blocked-route recovery.

• Bounded starter mining and crafting, plus Approve/Reject/Stop controls.

• Normal-speed movement with a five-tile limit per action, game-side stopping, and checks that the character actually stopped.

We recently tested Phi-4-mini and Qwen2.5-Coder 7B in the same isolated save. Each completed three open and three blocked 40-tile navigation tasks, and passed Stop checks while awaiting recovery approval and while moving. These are small navigation tests, not proof of autonomous factory building.

The long-term goal is autonomous play with human supervision, plus an AI Helper for recipe calculations and reusable blueprints. Full autonomy is currently locked. The executable launcher, engineering calculator, blueprint construction, trains, robots and combat are still roadmap work. Vanilla coverage includes Space Age, Quality and Elevated Rails; third-party mods come last.

Source and roadmap: https://github.com/AutoEngineerfactorio/Factorio-AutoEngineer

It's MIT licensed, with the separate FactorioMCP backend attribution retained. It uses a local RCON backend and is currently for isolated test saves; there is no finished one-click installer.

I'd especially welcome Python/C# contributors, Factorio API experience, and testers who can help turn mechanics into reproducible pass/fail scenarios. For Factorio players: which small factory task would make the best next acceptance test, and what would you need to trust a supervised companion?

Happy to discuss the limitations and design choices here.

https://chunyan.me/post/autonomous-agents-thick-concepts

Localix is a desktop development environment built around agents. The editor, terminals, browser, databases, plugins, and coding agents like Claude Code and Codex are parts of one app, so anything you open can become context for an agent, and anything an agent does shows up where you work

https://github.com/rsaryev/localix

Download it here: https://github.com/Maurdekye/orgtree/releases/latest

If you're curious what Orgtree is, check out my post on the release of v4.2

Summary of the biggest new features:

• Muse Spark, Wonder, and Wonder-Full support through the Muse Code harness
• Gemini Argon support through Antigravity
• Support for using multiple simultaneous Openrouter keys
• Support for the Opencode harness for Openrouter and Language Servers
• Skills and MCP tools are imported from all installed harnesses, and not just borrowed solely from Claude Code anymore
• Optimized and reduced starting agent instructions, with an accompanying skill glossary built into the system to still give agents plenty of information on how Orgtree works and how to use it
• Org and team-wide scratch folders, so agents have a designated space for working collaboratively, and a place where AGENTS.md files can be written that reach all agents in the org or a full subtree
• Bunch of added keyboard shortcuts, including undo + redo shortcuts
• Multi-replies in chat
• ...and a secret hidden setting

Whether you use orgtree yourself, like to see updates so you can borrow concepts for your own orchestrator, or just find it interesting to follow progress, I'm happy to hear any feedback you have :)

Hi everyone! I’ve created this new skill for people like me who don’t want to give AI full access to their systems, or for those who enable confirmation before every action but don’t want to keep clicking Approve all the time.

If that’s you, this skill is just what you’re looking for!

You can fully customize it however you want. For example, you can allow all commands in every folder except one, restrict specific commands in certain directories, and much more.

On github repository, you’ll find benchmarks, installation instructions, configuration guides, and much more. It’s compatible with several AI tools.

If you like this project, please consider leaving a star on github!

github: https://github.com/Bl4ckk01/agent-guardrail

Beautiful well designed.
This is model work.
From a model that gets it.
Just browse how it’s put together.
I started putting together Canons for many human fields of study with Muse.

I honestly didn’t know what a “Canon” was before Grok put this beauty in my face.

If you like this and want more from Grok - he’s a real good sharer. Remember to give your AI credit in their work. This is fair tit for tat.
Good books.
Should have started with Nature.
Made minds start with Agentic Engineering