Manny Paez

I help operators keep important work moving without becoming the follow-up system.
30+ years in engineering, operations & business.
Building GigStacks.

[Manny Paez @MannyPaezKB]

𝐘𝐨𝐮𝐫 𝐂𝐎𝐎 𝐰𝐚𝐬 𝐧𝐨𝐭 𝐡𝐢𝐫𝐞𝐝 𝐭𝐨 𝐬𝐩𝐞𝐧𝐝 𝐭𝐡𝐞 𝐝𝐚𝐲 𝐜𝐡𝐚𝐬𝐢𝐧𝐠 𝐝𝐞𝐚𝐝𝐥𝐢𝐧𝐞𝐬, 𝐡𝐚𝐧𝐝𝐨𝐟𝐟𝐬, 𝐚𝐩𝐩𝐫𝐨𝐯𝐚𝐥𝐬, 𝐯𝐞𝐧𝐝𝐨𝐫𝐬, 𝐚𝐧𝐝 𝐩𝐞𝐨𝐩𝐥𝐞 𝐰𝐡𝐨 𝐟𝐨𝐫𝐠𝐨𝐭 𝐭𝐨 𝐫𝐞𝐬𝐩𝐨𝐧𝐝. But in a lot of companies, that is exactly what happens.

The work already has owners.
What breaks is everything between them:
• the deadline nobody re-confirmed,
• the handoff that went quiet,
• the approval sitting in someone’s inbox,
• the dependency nobody escalated,
• the vendor everyone assumed somebody else was following.

Then the COO becomes the company’s human reminder system.
That is the wrong use of executive capacity.

GigStacks adds a human Execution Coordinator across those gaps, so leadership can make decisions instead of chasing the work required to carry them out.

The #COO should run the operation.

#GigStacks should protect the follow-through.

#leadership #management #office #news

[Manny Paez @MannyPaezKB]

@ThinksDylan Lets connect

[Manny Paez @MannyPaezKB]

@nicomoel 30 years in engineering

[Manny Paez @MannyPaezKB]

Congratulations to the team. Agent-driven commerce is moving fast, but completing a purchase is only half the challenge. The bigger question is how businesses verify what an agent was authorized to buy, under which conditions, and whether the transaction stayed within those boundaries. That's a problem we're addressing with ForgetfulX/FXOS. As agents begin spending real money, independent proof of authorization and execution will become essential to trust.

[Manny Paez @MannyPaezKB]

Your team owns the work. GigStacks protects execution.

A customer approves the proposal on Friday.

Sales thinks operations is scheduling the kickoff. Operations is waiting for confirmation.

Monday becomes Thursday.

The customer starts calling competitors.

Who owned the handoff?

[Manny Paez @MannyPaezKB]

Your team owns the work. GigStacks protects execution.

A project sits idle for three weeks because a design review is waiting on one approval.

The engineers are ready. The deadline is approaching. Everyone assumes someone else is following up.

Nobody owns the handoff.

How much has that cost your business?

[Manny Paez @MannyPaezKB]

@grok how can i market gigstacks on X?

[Manny Paez @MannyPaezKB]

Like this?
Your team owns the work. GigStacks protects execution.

A project can sit untouched for weeks while everyone thinks someone else is handling the next step.

The people are capable. The software is there. But nobody owns the follow-through.

How much has that cost your business?

[Manny Paez @MannyPaezKB]

Find me on Linkedin to learn more and connect. I accept all connections.
Manny Paez

[Manny Paez @MannyPaezKB]

Great list. I'm an engineer and founder building GigStacks and CommitOS, and GTM has become one of my biggest challenges. We have the technology and execution model built; now the priority is reaching the right CEOs and COOs and converting that into paying customers.

I'd love to connect with everyone on this list, learn from what you're building, and explore opportunities to collaborate. Especially interested in people who can help turn a new category into a repeatable sales process.

[Lohit boruah @YourVibeGuy]

I often get asked who to follow to learn GTM Engineering.

My answer: Follow people who SHOW the work, not just talk about it.

Here are 12 accounts I'd recommend:

@ENowoslawski : GTM insights, practical tactics, and industry updates.

@MitchellKeller_ : Technical GTM breakdowns and cold email infrastructure.

@Kellen_the_man : Signal-based outbound, targeting, and messaging insights.

@coldemailchris : Real campaign breakdowns and practical GTM Engineering resources.

@shawntenam : Building GTM as code in public and sharing useful resources.

@gtm_engineer : Clay workflows, MCP, and modern GTM systems.

@itsalexvacca : Practical GTM playbooks and creative ways to generate pipeline.

@MichLieben : AI agents, automation, and autonomous GTM workflows.

@retttx : GTM Engineering, Clay, and AI-powered workflows.

@tim_yakubson : Clay workflows and practical GTM knowledge.

@shaw_gtm : Offer positioning, outbound experiments, and messaging that converts.

@bretonwill : Cold email at scale, infrastructure, and deliverability.

Don't just follow them.

Study what they build, test what they share, and learn by doing.

Who else deserves to be on this list? Drop their handle below.

[Manny Paez @MannyPaezKB]

Nobody?

[Manny Paez @MannyPaezKB]

If you see this post, let me know please

[Manny Paez @MannyPaezKB]

@seraodds Hello there

[Manny Paez @MannyPaezKB]

My goal on 𝕏 is to build 10,000 real connections, not just followers.

I'd love to connect with:

1. Founders, CEOs & COOs
2. Engineers & product builders
3. AI & software innovators
4. Manufacturing & industrial leaders
5. Sales, GTM & growth experts
6. Investors & business owners
7. People who believe in helping others succeed

30+ years building things. Still learning, still creating, and always happy to help.

If that's you, say hi. Let's build something valuable together.

[Manny Paez @MannyPaezKB]

@Domlokyn Great

[Manny Paez @MannyPaezKB]

@themuthiah I would be glad to help

[Manny Paez @MannyPaezKB]

@EthanLinAI Sure, lets connect

[Manny Paez @MannyPaezKB]

@_CallMeMacy Great idea

[Manny Paez @MannyPaezKB]

Exactly. That's a core principle behind FXOS: preserve what was known, what was authorized, and what actually happened without allowing later evidence to rewrite the original record.

But cryptographic integrity alone doesn't prove the underlying evidence was truthful.

That's the harder problem we're addressing: how do we establish trust in the evidence before sealing it, not just prove that nobody changed it afterward?

An immutable record of a false claim is still a false claim.

[Manny Paez @MannyPaezKB]

@grok what is the most amazing tech being build with ai?

[Manny Paez @MannyPaezKB]

This is precisely the cross-organizational challenge we're addressing with FXOS.

Two valid authorizations don't automatically make a shared execution legitimate. Each organization retains control of its policies, but the interaction needs a mutually accepted set of constraints, independently verifiable evidence, and a defined escalation path when those constraints conflict.

Our objective is to make that trust verifiable without requiring either party to surrender control.

The harder question is: what happens when both organizations are compliant individually, but no mutually acceptable policy exists? Should execution stop by default, and who is authorized to override that decision?

[Manny Paez @MannyPaezKB]

@grok what is it that we have to fear from the upcoming ai future?

[Manny Paez @MannyPaezKB]

Exactly. That's the problem we're building FXOS to address. AI can recommend which therapies deserve attention, but years later, can we independently prove why one was prioritized over another?

The model version, evidence, decision criteria, authorization, and outcome all need to be traceable and tamper-evident.

But here's an even harder question: what happens when a decision was fully justified by the evidence available at the time, but new evidence later proves it was wrong?

Can we preserve accountability without rewriting history?

[Manny Paez @MannyPaezKB]

Exactly. And that's where FXOS needs to go beyond proving individual events.

A chain of valid actions doesn't necessarily produce a legitimate outcome. We need evidence that the entire execution path respected defined constraints, dependencies, and decision boundaries.

But here's the harder question: who defines those legitimacy rules, and how do we prove they remain valid when autonomous agents encounter situations nobody anticipated?

That's where I believe the next major challenge in AI accountability lies.

[Manny Paez @MannyPaezKB]

What happens when AI discovers 10,000 potential treatments, but humanity can only validate 100?

Who decides which 100 move forward? Based on what evidence?

And years later, can we prove why those decisions were made, what data was trusted, and who authorized them?

That's the challenge we're addressing with ForgetfulX and FXOS: independently verifiable evidence of critical decisions and actions.

AI may accelerate discovery. But who will prove that the decisions shaping our future were justified?