Eric Giguere (2026)

13/03/2026

𝗧𝗶𝗺𝗲 𝘁𝗼 𝗺𝗲𝗲𝘁 𝘁𝗵𝗲 𝗥𝗲𝗮𝗹 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗘𝘅𝗽𝗲𝗿𝘁 - 𝗣𝗿𝗼𝘂𝗱 𝘁𝗼 𝗶𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗲 𝗭𝗼𝗲 𝗛𝗮𝗿𝘁!

Most leaders don’t have a content problem.

𝗧𝗵𝗲𝘆 𝗵𝗮𝘃𝗲 𝗮 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁.

You likely have one message that consistently converts.

But it lives in one post.
One video.
One moment.

What if it became:
𝗠𝘂𝗹𝘁𝗶𝗹𝗶𝗻𝗴𝘂𝗮𝗹.
𝗧𝗲𝘀𝘁𝗲𝗱.
𝗥𝗼𝘂𝘁𝗲𝗱 𝗶𝗻𝘁𝗼 𝗖𝗥𝗠.
𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗶𝗻𝘁𝗼 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲.
𝗠𝗲𝗮𝘀𝘂𝗿𝗲𝗱 𝗮𝗴𝗮𝗶𝗻𝘀𝘁 𝗿𝗲𝘃𝗲𝗻𝘂𝗲.

𝗔𝗜 𝗮𝘃𝗮𝘁𝗮𝗿𝘀 aren’t about cloning yourself.

They’re about 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲.

In this 𝗔𝗜𝗔𝗕 𝘀𝗲𝘀𝘀𝗶𝗼𝗻, I walk through:
✔ The Cognitive Load Audit
✔ The 4-layer architecture
✔ The KPI stack that actually matters
✔ A 90-day implementation roadmap

If you’re still producing moments instead of assets, this will shift your thinking.

Full session + breakdown in the https://link.sixa1.com/sp/5d5e457851a below.

— Zoe Hart

12/03/2026

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗸𝗻𝗼𝘄 𝘁𝗵𝗲 𝗵𝗶𝗱𝗱𝗲𝗻 𝗰𝗼𝘀𝘁 𝗶𝗻 𝗺𝗮𝗻𝘂𝗮𝗹 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻?

Not production time.

𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝘀𝘄𝗶𝘁𝗰𝗵𝗶𝗻𝗴.

Every time you sit down to create a new video from scratch, you:
• Reset narrative tension
• Rebuild clarity
• Reconstruct delivery energy

That’s 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗯𝗮𝗻𝗱𝘄𝗶𝗱𝘁𝗵.

And executive bandwidth 𝗶𝘀 𝗳𝗶𝗻𝗶𝘁𝗲.

What if instead of recording more…
You encoded five core insights once
and deployed them structurally?

Not louder.

Smarter.

In 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 #𝟬𝟵 𝗼𝗳 𝗔𝗜𝗔𝗕, we’re walking through:
✔ The Cognitive Load Audit
✔ A 4-layer communication architecture
✔ KPI tracking beyond vanity metrics
✔ A 90-day shift from content to infrastructure

If you’re thinking seriously about scaling authority and pipeline — this one is different.
— Zoe

11/03/2026

𝗠𝗼𝘀𝘁 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝗱𝗼𝗻’𝘁 𝗵𝗮𝘃𝗲 𝗮 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗽𝗿𝗼𝗯𝗹𝗲𝗺.

They have a deployment constraint.

You likely have 𝗼𝗻𝗲 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 that consistently works.

𝗢𝗻𝗲 𝗳𝗿𝗮𝗺𝗶𝗻𝗴 that triggers real conversations.

𝗢𝗻𝗲 𝗶𝗻𝘀𝗶𝗴𝗵𝘁 clients repeat back to you.

And yet… You deploy it once.

Then you move on.
New video.
New post.
New angle.

Here’s the uncomfortable question:

If something converts…
𝘄𝗵𝘆 isn’t it architected to convert repeatedly?

We spend so much time creating.

Almost no time designing for compounding.

In our 𝗻𝗲𝘅𝘁 𝗔𝗜𝗔𝗕 𝘀𝗲𝘀𝘀𝗶𝗼𝗻, I’m going to challenge the way 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝘁𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝗔𝗜 𝗮𝘃𝗮𝘁𝗮𝗿𝘀.

Not as novelty.

Not as cloning.

But as communication infrastructure.

Because the difference between content and leverage
is 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲.

— Zoe Hart

10/03/2026

𝗢𝗻𝗲 𝗽𝗮𝘁𝘁𝗲𝗿𝗻 𝘀𝘁𝗼𝗼𝗱 𝗼𝘂𝘁 𝘄𝗵𝗶𝗹𝗲 𝘂𝗽𝗱𝗮𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝗤𝟭-𝟮𝟬𝟮𝟲 𝗔𝗜 𝗧𝗼𝗼𝗹𝘀 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸.

AI is moving from assistants → operators.

Tools with real agentic capability — able to plan and execute multi-step tasks — scored higher on ROI Time-to-Value than non-agentic tools in the same category.

It’s not a small gap.
It signals a structural shift.

Companies deploying 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗶𝗻 𝟮𝟬𝟮𝟲 will not be doing the same work faster.
They’ll be doing different work entirely.

The latest benchmark release breaks down:
• the 𝟰 𝗳𝗼𝗿𝗰𝗲𝘀 𝗿𝗲𝘀𝗵𝗮𝗽𝗶𝗻𝗴 𝘁𝗵𝗲 𝗔𝗜 tool landscape
• why 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺𝘀 are pulling ahead
• which tools are approaching 𝗰𝗮𝘁𝗲𝗴𝗼𝗿𝘆 𝘂𝗽𝗴𝗿𝗮𝗱𝗲𝘀
• which tools quietly disappeared

Because the question isn’t:
“What AI tool should we try next?”

It’s:
“What 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 are we actually building?”

09/03/2026

𝗧𝗵𝗶𝘀 𝗾𝘂𝗮𝗿𝘁𝗲𝗿 𝟭𝟯𝟬 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀 𝗱𝗶𝘀𝗮𝗽𝗽𝗲𝗮𝗿𝗲𝗱 𝗳𝗿𝗼𝗺 𝗼𝘂𝗿 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸.

Not because they failed.
Because the floor moved.

Consumer avatar tools.
Standalone writing assistants.
Niche generators.

𝗧𝗵𝗲𝘀𝗲 𝘄𝗲𝗿𝗲 𝗿𝗲𝗮𝗹 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 𝘄𝗶𝘁𝗵 𝗿𝗲𝗮𝗹 𝘂𝘀𝗲𝗿𝘀.

A year ago several of them would have been on shortlists.

They aren't anymore.

The 𝗤𝟭-𝟮𝟬𝟮𝟲 𝗔𝗜 𝗧𝗼𝗼𝗹𝘀 & 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝗠𝗮𝗿𝗸𝗲𝘁 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸 evaluates:
• 250 tools
• across 15 categories
• using a 40-criteria scoring framework

𝟭𝟬,𝟬𝟬𝟬+ 𝗱𝗮𝘁𝗮 𝗽𝗼𝗶𝗻𝘁𝘀.

And four signals are 𝗿𝗲𝘀𝗵𝗮𝗽𝗶𝗻𝗴 𝘁𝗵𝗲 𝗺𝗮𝗿𝗸𝗲𝘁:
1️⃣ 𝗔𝗴𝗲𝗻𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻
AI shifting from assistants to autonomous operators
2️⃣ 𝗠𝗼𝗻𝗲𝘁𝗶𝘀𝗮𝘁𝗶𝗼𝗻 𝗿𝗲𝘀𝗲𝘁
Freemium models disappearing
3️⃣ 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗽𝗿𝗲𝘀𝘀𝘂𝗿𝗲
Security and ethics becoming baseline requirements
4️⃣ 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗴𝗿𝗮𝘃𝗶𝘁𝘆
Microsoft, Google and Amazon ecosystems pulling tools inward

The takeaway is simple.

Organizations that treat AI as a collection of tools will always be chasing.

Organizations that treat AI as architecture will compound advantage.

https://link.sixa1.com/sp/ac7b81c066b

24/02/2026

Ever heard the expression:
‘𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗘𝗻𝗱 𝗶𝗻 𝗠𝗶𝗻𝗱’?

Here’s a quiet truth about a virtual 𝗦𝗗𝗥:

Integration is not automatic 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲.

You can 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 five tools and still have 𝗻𝗼 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗹𝗮𝘆𝗲𝗿.

You can 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗲𝗻𝗿𝗶𝗰𝗵𝗺𝗲𝗻𝘁 and 𝘀𝘁𝗶𝗹𝗹 𝗹𝗮𝗰𝗸 𝗾𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 thresholds.

You can 𝘁𝗿𝗶𝗴𝗴𝗲𝗿 sequences and still damage the brand silently.

The 𝗿𝗲𝗮𝗹 𝗺𝗮𝘁𝘂𝗿𝗶𝘁𝘆 shift isn’t more automation.

It’s 𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲.

And that’s what you should 𝗞𝗲𝗲𝗽 𝗶𝗻 𝗠𝗶𝗻𝗱.

24/02/2026

𝗠𝗼𝘀𝘁 𝘁𝗲𝗮𝗺𝘀 𝘀𝗮𝘆 𝘁𝗵𝗲𝘆’𝘃𝗲 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗼𝘂𝘁𝗯𝗼𝘂𝗻𝗱.

But automation isn’t the same as infrastructure.

If signal volume 𝗱𝗼𝘂𝗯𝗹𝗲𝗱 tomorrow,
Would your CRM 𝘀𝘁𝗮𝘆 𝗰𝗹𝗲𝗮𝗻?
Would routing 𝗿𝗲𝗺𝗮𝗶𝗻 𝗱𝗶𝘀𝗰𝗶𝗽𝗹𝗶𝗻𝗲𝗱?
Would reporting 𝗿𝗲𝗺𝗮𝗶𝗻 𝘁𝗿𝘂𝘀𝘁𝘄𝗼𝗿𝘁𝗵𝘆?

AI lowers the cost of sending.
It doesn’t lower the cost of poor architecture.

Session #08 explores the difference between speed…
and Strength.

20/02/2026

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗽𝘂𝘁 𝗮𝗻 𝗲𝗻𝗱 𝘁𝗼 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗯𝘂𝘁 𝘂𝘀𝗲𝗹𝗲𝘀𝘀 𝘄𝗼𝗿𝗸?

In AIAB Session #07, 𝗝é𝗿é𝗺𝘆 𝗚𝗿𝗮𝗻𝗱𝗶𝗹𝗹𝗼𝗻 reminded us of something important:

Signals matter more than volume.
Automation should remove friction — not replace people.

𝗧𝗵𝗮𝘁’𝘀 𝗮 𝗺𝗮𝘁𝘂𝗿𝗶𝘁𝘆 𝘀𝗵𝗶𝗳𝘁.

But if we zoom out, AI adoption itself has evolved in clear stages:
𝗣𝗵𝗮𝘀𝗲 𝟭 — Foundation
LLMs learned to read and write.
𝗣𝗵𝗮𝘀𝗲 𝟮 — Conversation
They learned to “chat” — to reason interactively.
𝗣𝗵𝗮𝘀𝗲 𝟯 — Workflow Integration
We started asking:
“Where can we automate?”
Tools connected. Triggers activated. Processes accelerated.

Now we’re entering the next phase.

𝗣𝗵𝗮𝘀𝗲 𝟰 — Orchestration & Governance
How do we design this so it scales without breaking?
How do we protect CRM?
How do we enforce routing discipline?
How do we ensure predictability under volume?

As 𝗣𝗲𝘁𝗲𝗿 𝗗𝗿𝘂𝗰𝗸𝗲𝗿 warned:
“T𝘩𝘦𝘳𝘦 𝘪𝘴 𝘯𝘰𝘵𝘩𝘪𝘯𝘨 𝘴𝘰 𝘶𝘴𝘦𝘭𝘦𝘴𝘴 𝘢𝘴 𝘥𝘰𝘪𝘯𝘨 𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘵𝘭𝘺 𝘵𝘩𝘢𝘵 𝘸𝘩𝘪𝘤𝘩 𝘴𝘩𝘰𝘶𝘭𝘥 𝘯𝘰𝘵 𝘣𝘦 𝘥𝘰𝘯𝘦 𝘢𝘵 𝘢𝘭𝘭.”undefined

Efficiency without orchestration amplifies vulnerability.

Session #07 showed us how to design smarter GTM engines.

Session #08 builds on that foundation — exploring what happens when an AI SDR becomes governed revenue infrastructure.

Same evolution. Higher altitude.

18/02/2026

𝗢𝗻𝗹𝘆 𝟮𝟳% 𝗼𝗳 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗿𝗲𝗽𝗼𝗿𝘁 𝗥𝗢𝗜 𝗳𝗿𝗼𝗺 𝗔𝗜 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻

Last week in AIAB Session #07, 𝗝é𝗿é𝗺𝘆 𝗚𝗿𝗮𝗻𝗱𝗶𝗹𝗹𝗼𝗻 (𝗧𝗖𝟵) walked us through something critical:

GTM automation isn’t about tools.
It’s about signals, structure, and adoption.

One line stayed with me:
“Automation should remove friction — not replace people.”

That framing matters.

Because here’s the tension many leaders feel:

If automation increases speed…
why doesn’t it always increase predictability?

According to 𝗠𝗰𝗞𝗶𝗻𝘀𝗲𝘆’𝘀 𝟮𝟬𝟮𝟯 𝗚𝗹𝗼𝗯𝗮𝗹 𝗦𝘂𝗿𝘃𝗲𝘆 𝗼𝗻 𝗔𝗜,
only 27% of companies report significant bottom-line impact from AI adoption.
(Source: McKinsey Global Survey on AI, 2023)

Why?

Because most organizations automate tasks.

Very few R𝗲𝗱𝗲𝘀𝗶𝗴𝗻 S𝘆𝘀𝘁𝗲𝗺𝘀.

Session #07 helped us think in terms of GTM engines.

Session #08 builds from that foundation:

What happens when an AI-driven SDR becomes governed revenue infrastructure?

Same evolution.

Next layer.

13/02/2026

𝗔𝗜 𝗶𝗻 𝗚𝗧𝗠 𝗶𝘀𝗻’𝘁 𝘁𝗵𝗲 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲.

A GTM engine built on signals, precision, and ex*****on velocity is.

Most teams use AI to speed up outputs.

But the real ROI shows up when AI becomes part of the workflow system: capturing signals, filtering noise, qualifying properly, and activating only what matters.

That’s what we unpack in AIAB Session #07 with Jérémy Grandillon.

See you inside!

— Eric @ SIX:A1

11/02/2026

𝗬𝗼𝘂’𝗿𝗲 𝘂𝘀𝗶𝗻𝗴 𝗔𝗜… 𝗯𝘂𝘁 𝗚𝗧𝗠 𝘀𝘁𝗶𝗹𝗹 𝗳𝗲𝗲𝗹𝘀 𝗽𝗮𝗶𝗻𝗳𝘂𝗹𝗹𝘆 𝗺𝗮𝗻𝘂𝗮𝗹?

Most teams already have AI in the stack.

And yet the same reality remains:
Research still takes hours.
Lead quality is still uneven.
Teams still burn time on low-signal work.

That’s the 𝗿𝗲𝗮𝗹 𝗔𝗜 - 𝗥𝗢𝗜 𝗴𝗮𝗽.

In 𝗔𝗜𝗔𝗕 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 #𝟬𝟳, with , we break down why GTM automation only creates leverage when AI becomes part of the ex*****on system — not just a productivity layer.

This isn’t about prompts.

It’s about 𝘀𝗶𝗴𝗻𝗮𝗹𝘀 → 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 → 𝗮𝗰𝘁𝗶𝘃𝗮𝘁𝗶𝗼𝗻 → 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗹𝗼𝗼𝗽𝘀.

👉 Read the full article here: https://www.linkedin.com/pulse/what-actually-changes-when-ai-becomes-part-gtm-eric-giguere-c7w0e

— Eric @ SIX:A1

07/02/2026

𝗛𝗲𝗿𝗲’𝘀 𝗮 𝗰𝗼𝘂𝗻𝘁𝗲𝗿𝗶𝗻𝘁𝘂𝗶𝘁𝗶𝘃𝗲 𝘁𝗿𝘂𝘁𝗵 𝗮𝗯𝗼𝘂𝘁 𝗔𝗜 𝗶𝗻 𝗴𝗼-𝘁𝗼-𝗺𝗮𝗿𝗸𝗲𝘁

If you automate something that isn’t clearly understood,
you don’t gain leverage — you scale confusion.

Most GTM automation failures aren’t technology failures.
They’re process failures, amplified by speed.

The teams seeing real ROI from AI aren’t doing “more outreach.”

They’re filtering harder, activating later, and designing workflows around signals — not volume.

I’m preparing an AIAB session with Jérémy Grandillon (https://link.sixa1.com/sp/34ac52b2b13), who breaks this down with real-world GTM systems, not theory.

If GTM still feels manual despite AI in the stack, this one will resonate.

— Eric @ SIX:A1

Eric Giguere

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