ForwardThinking 🤔

Agents here, there and nowhere

We’ve all heard the relentless hype around AI agents. They will be so potent they will come for our jobs, our software, our workflows. Agentic workforces will force an all-encompassing overhaul of how we do business. Wall Street has bought into this vision so completely, it is starting to question the value of many SaaS stocks.

At this point, it's clear that AI is highly proficient at tasks like coding, even if our current approaches to automated coding could be flawed. But that’s not the real issue. The harder question is whether enterprises can overcome the inherent complexity of making such a sweeping change inside large organizations.

AI agents might indeed be coming, but getting real value will require coordinated, organization-wide changes, and as we’ve seen with past technological shifts, large enterprises often struggle to pull all the pieces together.

For agents to work right, we will need clean data, rock-solid security, clear observability, strong guardrails and smooth integrations with other tools. We will also need humans writing crystal clear prompts, and the agents they produce communicating with one another as they interact and move across systems. While the Agent2Agent and MCP protocols are supposed to solve the communication problems, many are what my former boldstart colleague Ed Sim called the hard last-mile problems. These won't be resolved easily, no matter how much hype the industry throws at us.

My agentic adventure

As I often do in this space, I want to tell a personal story about working with this technology. I realize I'm just one person, but if I have trouble building agents within my narrow use case, it speaks to the difficulties of scaling inside a large company.

I spent a couple of frustrating days trying to get Claude to build a fairly modest agent, one I've built before with other tools, so it was a good test. Each morning the agent needs to deliver me the latest tech headlines to my Gmail inbox. It involves building a scheduler, integrating with Gmail, searching for headlines and understanding what constitutes news. To simplify matters, I asked the Claude chatbot to write me the prompt to use with Claude Cowork, the agent builder. It still took a lot of frustrating back and forth before it finally built what I wanted.

Even then, I found that it was concentrating too much on one publication, or wasn't casting its search widely enough. I had to tell it not to use more than two headlines from any single publication, and to cast a wider net by pulling in additional outlets it wasn't including. This kind of tweaking continued, and I still don't have quite what I want.

Now take this small example, and imagine you are trying to build an agent for a complex enterprise workflow. The problems you are likely to encounter just describing the set of tasks are going to multiply, and it will grow increasingly difficult to get the agent doing exactly what you envision. There will be some off-the-shelf tools like coding agents, but the more customization you need, the harder it's going to be to build an agent that can smoothly complete your tasks.

The multi-agent conundrum

Now imagine you are trying to get 10 agents working in tandem, all within an organization mired in technical debt with messy data spread out across numerous systems where you have to build a standard way of securing and governing these tools. The challenges just get bigger than my simple experiment, which is to say the hype is great, but the reality is clearly another matter.

Let's say you get a complex agent doing what you want, the next challenge is getting it to work with other agents, and figuring out what to do when the workflow breaks or throws a curve, something humans inherently understand. We adapt and build work-arounds. Will an agent smoothly fix a problem, kick it out to a human, go into a loop (costing valuable tokens) or stop working altogether?

Then think about a project involving humans. Jeff Bezos popularized the “two‑pizza rule” at Amazon, meaning a team should be small enough to be fed with just two pizzas. He recognized that once a team grows beyond a certain size, bureaucracy creeps in and the group becomes less efficient and less effective.

It stands to reason that the two-pizza rule could apply to agents too, even though they don't eat, sleep or stop working. Research suggests that the more agents you add, the worse they perform. A recent study found multi‑agent groups actually did worse than a single agent as coordination overhead mounted, mirroring what happens when human teams get too large.

None of this is to say you should just throw up your hands and give up, but you should be aware that the hype doesn't necessarily match the reality yet. In this case, the emperor may actually have clothes, but you’re going to have to sew them yourself and make sure they fit correctly.

~Ron

What's new on the blog 📰

How one person is securing all of Amazon from front door to firewall

Amazon is a huge company and when you consider subsidiaries like Whole Foods and MGM Studios, it's even bigger. That's why it's so hard to believe that one person is in charge of integrated security across the company for everything from badges to cyber.

I spoke to that person and learned why the company thinks it's important to take this approach.

Read full Article>>

As Narayen steps down, Adobe must confront its next big transition

Last week, Shantanu Narayen announced he was stepping down as Adobe CEO after 18 years on the job. He oversaw some major transformations in his time in the corner office, including the move from boxed software to cloud subscriptions, but with his departure, the company may be facing its biggest transition yet.

Read full article>>

Amazon is betting big that OpenAI stays relevant

In the latest collaboration from me and Alex Wilhelm, we take a deep dive into the recent Amazon investment in OpenAI that could be worth as much as $50 billion.

The question is: Is Amazon getting in too late for too much money, or are they getting a piece of what will turn out to be lucrative action in spite of the timing.

Read full article>>

AI-generated code is flooding the software supply chain with new threats

While it’s undeniable that AI coding tools make it easier to generate code faster and more efficiently, that new velocity is also introducing risks to the software supply chain that can’t be swept under the rug.

I spoke with Cassie Crossley, author of Software Supply Chain Security, about how AI is changing the threat landscape, and why caution should be the watchword.

"You can't know every single library, and frankly, there are not enough security layers built in yet for vibe coding that I would ever trust at the moment."

Read full article>>

A SaaS pioneer confronts the rise of AI

As the SaaS relevancy debate in the age of AI rages on, I spoke to a SaaS pioneer, Tien Tzuo. He's CEO at subscription billing platform Zuora, and was employee #11 at Salesforce.

He doesn’t sugarcoat the threat AI poses to SaaS when he says, "Can AI versions of an enterprise software category replace a non-AI version? It's absolutely going to happen. How could it not?"

But he also argues that SaaS companies still have distinct advantages that vibe coding alone can’t match.

Read full article>>

News of the Week 📣

Zendesk is acquiring CX AI startup Forethought

Zendesk announced this week that it intends to buy customer experience AI startup Forethought. The companies did not reveal the acquisition cost.

Forethought exploded onto the scene in 2018 when it won the TechCrunch Disrupt Battlefield competition. I wrote about the company ahead of the event, and at the time, it was building a plain language enterprise search engine at a time when most search engines were concentrating on keyword search.

The company eventually zeroed in on a customer service use case, then evolved into a chatbot before more recently shifting to an agent‑focused approach. It was this final shift that attracted Zendesk as a buyer.

“Forethought’s advanced capabilities perfectly align with our vision for agentic service," Zendesk CEO Tom Eggemeier said in a statement. The good news for Forethought customers is that Zendesk promises "uninterrupted service and continued product innovation." If that turns out to be the case, that would be the best case scenario for existing customers.

Forethought was founded in 2017 and raised $117 million along the way, per Crunchbase data. The most recent raise was $25 million last May. A fun fact about the company is that actress Gwyneth Paltrow was an investor.

Microsoft overhauls its Copilot leadership team

Microsoft shuffled its AI leadership team this week, consolidating its consumer and enterprise Copilot efforts under a single executive. That executive is Jacob Andreou, a former Snap product leader who had been overseeing product and growth for consumer Copilot at Microsoft.

Previously, consumer AI products sat under Mustafa Suleyman, who now shifts his focus to model development and what Microsoft describes as “superintelligence,” a still‑vague effort to build more advanced AI systems. In practice, Suleyman will concentrate on research and frontier models rather than running the day‑to‑day Copilot business.

While Microsoft has framed the move as a straightforward reorg to unify a fragmented Copilot organization under one leader reporting directly to CEO Satya Nadella, it’s also easy to read it as a sign that Nadella wants clearer accountability as Copilot faces increasing competition from the AI labs.

This week in startups

• Standard Template Labs, a new startup from former Datadog president Amit Agarwal, launched this week with $49 million in funding at a $300 million valuation, per Bloomberg. The company is taking aim at industry stalwarts like ServiceNow and Atlassian by building an AI-fueled IT service platform designed to help resolve incident tickets automatically.
• Cloud-native security startup Scanner announced a $22 million Series A this week. The company, which was founded in 2022, provides a centralized security data platform and uses the Model Context Protocol (MCP) to enable AI agents to analyze that data for potential issues before they escalate.
• In an effort to deepen the tooling around its Codex development platform, OpenAI announced this week that it plans to acquire Astral, a startup that builds widely used open source Python tools for developers. The deal brings both Astral’s team and its toolchain (including uv, Ruff, and ty) into Codex, giving OpenAI in‑house control of key developer utilities as well as the talent behind them.

What I'm reading 📚

The AI coding hangover
~By David Linthicum, InfoWorld

Agents of Chaos
~By Natalie Shapiro, et al, David Bau Labs

‘Yes, AI Is a Bubble. There Is No Question.’
~By Derek Thompson, Derek Thompson blog

12 most misused buzzwords in IT
~By Mary K Pratt, CIO.com

Look who's talking 👄

"It’s not a single invention that creates exponential growth—it’s the constant compounding of innovation, one idea building on another, again and again."

~Michael Wu, Chief AI Strategist at PROS, from his keynote address at CRM Playaz IRL 2026.