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Beyond Zapier

Beyond Zapier: What Happens When Workflow Automation Becomes Obsolete?

By Skeeter Wesinger August 3, 2025

For years, tools like Zapier, LangChain, and Make (formerly Integromat) have served as the backbone of modern automation. They gave us a way to stitch together the sprawling ecosystem of SaaS tools, APIs, and data triggers that power everything from startups to enterprise platforms. They democratized automation, enabled lean teams to punch above their weight, and brought programmable logic to non-programmers.

But here’s the uncomfortable truth: their days are numbered.

These platforms weren’t designed to think—they were designed to follow instructions. They excel at task execution, but they fall short when the situation requires adaptation, judgment, or real-time negotiation between competing priorities. The problem isn’t what they do; it’s what they can’t do.

The Next Frontier: Intent-Driven Autonomy

The future doesn’t belong to systems that wait to be told what to do. It belongs to systems that understand goals, assess context, and coordinate actions without micromanagement. We’re entering the age of intent-driven autonomy, where AI agents don’t just execute; they plan, adapt, and negotiate across domains.

Imagine a world where your AI agent doesn’t wait for a Zap to send an email—it anticipates the follow-up based on urgency, sentiment, and your calendar. Where you don’t need to build a LangChain flow to summarize documents—your agent reads, tags, stores, and cross-references relevant data on its own. Where infrastructure no longer needs triggers because it has embedded agency—software that adjusts itself to real-world feedback without human intervention.

This is more than automation. This is cognition at the edge of software.

Why This Isn’t Hype

We’re already seeing signs. From autonomous GPT-based agents like AutoGPT and CrewAI to self-updating internal tools powered by vector databases and real-time embeddings, the scaffolding of tomorrow is under construction today. These agents won’t need workflows—they’ll need guardrails. They’ll speak natural language, interact across APIs, observe results, and self-correct. And instead of chaining actions together, they’ll pursue objectives.

Don’t Panic. But Do Prepare.

This doesn’t mean Zapier or LangChain failed. On the contrary, they paved the way. They taught us how to think modularly, how to connect tools, and how to make systems work for us. But as we move forward, we need to unlearn some habits and embrace the shift from rigid logic to adaptive intelligence.

The question for builders, founders, and technologists isn’t “What should I automate next?” It’s “What kind of agency am I ready to give my systems?”

Because the future isn’t about building better workflows. It’s about building systems that don’t need them.

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Burning the Future

Burning the Future: Why Waymo Robotaxis Are Being Targeted in Los Angeles

By Skeeter Wesinger
June 11, 2025

The future is burning in Los Angeles—and it’s driving itself into the flames.
In recent weeks, autonomous vehicles operated by Waymo, Alphabet’s self-driving subsidiary, have become a flashpoint in the city’s ongoing social unrest. What began as scattered protests against housing inequality and police overreach has turned sharply against the most visible emblem of Silicon Valley’s quiet conquest of urban life: the driverless car.
Waymo’s robotaxis—sleek, sensor-laden electric vehicles that glide through city streets with no one at the wheel—have been set on fire, spray-painted, disabled, and blocked. In some cases, protesters jumped on their hoods. In one instance, the vehicle’s lithium-ion battery ignited, blanketing an intersection in black smoke and toxic fumes. Five cars were torched in a single night near the Beverly Center. Waymo has since suspended service in key areas.
Why Waymo? Why now?

A Rolling Surveillance State
Part of the answer lies in optics. A Waymo car looks like what it is: a surveillance platform in motion. Packed with LiDAR, radar, and 360-degree cameras, each vehicle is effectively a roving sensor array collecting vast troves of visual and environmental data. Protesters increasingly believe that Waymo footage is being shared—or could be shared—with law enforcement. That makes the robotaxi a surveillance threat, especially in communities already skeptical of over-policing and state monitoring.
In an age when public space is contested ground, a driverless car is not just an anomaly—it’s a trespasser.

Automation as Class War
But the backlash isn’t only about privacy. For many in Los Angeles, Waymo represents something even more existential: job loss at the altar of automation.
The city’s economy still depends on tens of thousands of human drivers—Uber, Lyft, taxis, delivery vans, and commercial transport. Waymo’s expansion signals a not-so-distant future in which those workers are rendered obsolete. That future is arriving without public input, without protections, and with little concern for who gets left behind. The Teamsters and the LA County Federation of Labor have protested Waymo’s rollout since 2023. Their warnings are now finding a wider audience, and a louder voice.
If you’re looking for a symbol of job displacement and unaccountable tech governance, you won’t find a better target than a car that drives itself and costs a man his living.

Tech as the Face of Gentrification
There’s also the unavoidable truth that Waymo vehicles are highly visible in neighborhoods already under pressure from gentrification. The sleek, whirring robotaxis feel alien, indifferent—like emissaries of a world that values efficiency over community, and sensors over people. For longtime residents, they are reminders of a city being hollowed out, algorithm by algorithm, until only the surface remains.
In this context, setting a Waymo car on fire is not just an act of destruction. It is a political statement.

Spectacle and Strategy
And then there’s the media effect. A burning Waymo is headline gold. It’s instantly legible as a rejection of Big Tech, of automation, of surveillance, of the inequality that comes when luxury innovation is layered on top of public neglect. Images of charred autonomous vehicles make the evening news, circulate on social media, and galvanize protestors elsewhere.
It’s not unlike what the Luddites did in the 19th century—targeting the machines that symbolized their displacement. Only now the machine drives itself and livestreams the revolution.

A Dangerous Road Ahead
Waymo’s executives are right to be concerned. What’s being targeted isn’t just a brand—it’s a future that many people were never asked to vote on. One where machines replace people, where public spaces are privately surveilled, and where “innovation” often means exclusion.
The destruction of these vehicles may be unlawful, but the message is clear: you can’t automate your way out of accountability.
Until the tech industry confronts this unrest not with PR statements but with real dialogue, real reform, and a real respect for the communities it drives through, the streets will remain dangerous, not just for Waymos but for any vision of the future that forgets the people in the present.

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McKinsey Has a Bot for That

How AI is quietly taking over the consulting industry—from slide decks to strategy sessions.

By Skeeter Wesinger
June 10, 2025

Let’s say you’re the CEO of a Fortune 500 company. You’ve just paid McKinsey a few million dollars to help streamline your supply chain or finesse your M&A pitch. What you may not know is that some of that brainpower now comes from a machine.

McKinsey, Bain, and Boston Consulting Group—the Big Three of strategy consulting—have embraced artificial intelligence not just as a service they sell, but as a co-worker. At McKinsey, a proprietary AI platform now drafts proposals, generates PowerPoint decks, and even outlines market entry strategies. That used to be a junior analyst’s job. Now it’s done in seconds by software.

The firm insists this is progress, not replacement. “Our people will be doing the things that are more valuable to our clients,” a McKinsey spokesperson told the Financial Times.¹ It’s the kind of line that sounds better in a press release than in a staff meeting.

Meanwhile, Bain & Company has rolled out a custom chat interface powered by OpenAI.² It’s more than just a chatbot—it’s a digital consigliere that surfaces insights, runs simulations, and drafts client memos with GPT-powered fluency. Over at Boston Consulting Group, AI-driven engagements already make up 20 percent of the firm’s total revenue.³ That’s not a rounding error—it’s a shift in the business model.

This Isn’t Just Efficiency. It’s a Redefinition.

AI doesn’t sleep, bill overtime, or ask for a promotion. It digests case studies, slurps up real-time market data, and spins out “insights” at breakneck speed. A proposal that once took two weeks now gets turned around in two hours. A slide deck that required a team of Ivy Leaguers is built by algorithms trained on millions of prior decks.

That’s the efficiency part. But the real story is what happens next.

Strategy consulting has always sold scarcity—the idea that elite firms offered unique, human insight. But what happens when AI systems trained on decades of reports can replicate that thinking, and maybe even improve on it?

“Empathy,” the firms say. “Judgment.” “Relationship building.” Those are the buzzwords that now define human value in consulting. If the machine can do the math, the humans must do the trust. It’s a plausible pivot—until clients bring their own AI to the table.

The Consultants Are Pivoting—Fast

McKinsey and its rivals aren’t fighting the change—they’re monetizing it. They’re building internal tools while also selling AI implementation strategies to clients. In effect, they’re profiting twice: first by automating their own work, then by teaching others how to do the same.

This is the classic consulting playbook—turn a threat into a line item.

But beneath the slideware optimism is an existential question. If your AI builds the deck, drafts the strategy, and even suggests the pricing model, what exactly are you buying from a consultant?

Maybe it’s still the name on the invoice. Maybe it’s the assurance that someone—some human—stands behind the recommendation. Or maybe, just maybe, it’s the beginning of a new normal: where the smartest person in the room isn’t a person at all.

Citations

  1. Mark Marcellis, “McKinsey’s AI Revolution Has Begun,” Financial Times, May 29, 2025. https://www.ft.com/content/mckinsey-ai-presentation-tools
  2. Derek Thompson, “How Bain Is Using OpenAI to Redefine Consulting,” The Atlantic, March 12, 2025. https://www.theatlantic.com/technology/bain-openai-strategy
  3. David Gelles, “At BCG, AI Consulting Now Drives 20% of Revenue,” The New York Times, April 10, 2025. https://www.nytimes.com/business/bcg-ai-revenue-growth
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The age of Generative AI

The advent of Generative AI (GenAI) has begun to transform the professional services sector in ways that are reminiscent of past industrial shifts. In pricing models, particularly, GenAI has introduced an undeniable disruption. Tasks once demanding hours of meticulous human effort are now being automated, ushering in a reduction of operational costs and a surge in market competition. Consequently, firms are being drawn towards new pricing paradigms—cost-plus and competitive pricing structures—whereby savings born of automation are, at least in part, relayed to clients.

GenAI’s influence is most visible in the routinized undertakings that have traditionally absorbed the time and energy of skilled professionals. Drafting documents, parsing data, and managing routine communications are now handled with remarkable precision by AI systems. This liberation of human resources allows professionals to concentrate on nuanced, strategic pursuits, from client consultation to complex problem-solving—areas where human intellect remains irreplaceable. Thus, the industry drifts from the conventional hourly billing towards a value-centric pricing system, aligning fees with the substantive outcomes delivered, not merely the hours invested. In this, GenAI has flattened the landscape: smaller firms, once marginalized by the resources and manpower of larger entities, can now stand as credible competitors, offering similar outputs at newly accessible price points.

Further, the rise of GenAI has spurred firms to implement subscription-based or tiered pricing models for services once bespoke in nature. Consider a client subscribing to a GenAI-powered tool that provides routine reports or documentation at a reduced rate, with options to escalate for human oversight or bespoke customization. This hybrid model—where AI formulates initial drafts and human professionals later refine them—has expanded service offerings, giving clients choices between an AI-driven product and one fortified by expert review. In this evolving terrain, firms are experimenting with cost structures that distinguish between AI-generated outputs and those augmented by human intervention, enabling clients to opt for an economical, AI-exclusive service or a premium, expert-reviewed alternative.

Investment in proprietary GenAI technology has become a distinguishing factor among leading firms. To some clients, these customized AI solutions—tailored for fields such as legal interpretation or financial forecasting—exude an allure of exclusivity, thereby justifying the elevated fees firms attach to them. GenAI’s inherent capacity to track and quantify usage has also paved the way for dynamic pricing models. Here, clients are billed in direct proportion to their engagement with GenAI’s capabilities, whether through the volume of reports generated or the features utilized. In this, professional services firms have crafted a usage-based pricing system, a model flexible enough to reflect clients’ actual needs and consumption.

However, with progress comes the shadow of regulation. As governments and regulatory bodies move to address GenAI’s ethical and data implications, professional service firms, particularly in sensitive sectors like finance, healthcare, and law, may find themselves bearing the weight of compliance costs. These expenses will likely be passed on to clients, especially where data protection and GenAI-driven decision-making demand rigorous oversight.

In the aggregate, GenAI’s integration is compelling professional services firms towards a dynamic, flexible, and transparent pricing landscape—one that mirrors the dual efficiencies of AI and the nuanced insights of human expertise. Firms willing to incorporate GenAI thoughtfully are poised not only to retain a competitive edge but also to expand their client offerings through tiered and value-based pricing. The age of GenAI, it seems, may well be one that redefines professional services, merging the best of human acumen with the swift precision of artificial intelligence.

Skeeter Wesinger

November 8, 2024

https://www.linkedin.com/pulse/age-generative-ai-skeeter-wesinger-oe7pe

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