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Workflow Evolution
Comparison of traditional vs. agent-assisted workflow efficiency.
Primary Sources
When Agents Work for the Whole Team - LinkedIn
When every role can prompt agents, validate in real time, and move work forward directly, the handoffs stop piling up. Here's what that looks like in practice. When companies adopt AI coding tools, the workflow usually looks like this: developers gain access, individual contributor productivity increases, and delivery timelines remain flat. AI made developers faster at the one step they already owned, and left everything around that step exactly as it was. The teams closing the gap between AI promise and actual delivery throughput are taking a different approach. They're putting agents in the hands of the whole product team, not just the engineers. What the standard workflow is actually costing you The standard product workflow is sequential by design. A PM defines the work, a designer shapes it, an engineer builds it, and QA validates it. Each step waits for the previous one to finish, and each handoff carries a queue. This structure made sense when it was built because code was genuinely expensive to produce. Every change had to flow through the one function that could produce it. Everything before coding was prep work, meant to ensure engineers didn't have to recode anything once they got started. That assumption is now outdated. Agents can produce working code from a prompt, and the cost of generating a first implementation has dropped close to zero. The question is no longer whether your team can afford to code something; it's who gets to write the prompt. When only developers interact with agents, the sequential structure stays intact. Designers file redlines and wait for engineers to interpret them. PMs write specs that sit in sprint backlogs. QA waits until something is nearly finished before testing it. Engineers field clarification questions that interrupt their focus. Making the coding step faster doesn't change any of that. The workflow moves quickly in one narrow lane and at the same pace everywhere else. What changes when the whole team has access When every role can interact directly with agents, the sequential structure begins to collapse. A designer can refine spacing and interactions directly in code without having to file a redline. A PM can turn a ticket into a working prototype without opening a Jira comment thread. QA can reproduce a bug, prompt a fix, and verify it in the same session. None of that work needs to touch an engineer until it's already been reviewed and validated by the people who would have generated rework cycl...
I built an agent to do my job. Then it hung up on my boss.
Amanda Hoover; Alyssa Powell/BI I built my replacement I let an AI agent do my job for a week. It thinks my boss is an idiot. Amanda Hoover; Alyssa Powell/BI By Amanda Hoover You're currently following this author! Want to unfollow? Unsubscribe via the link in your email. 2026-05-01T08:07:01.292Z Rather than wait to find out if AI will replace me, I built my replacement.Big Tech execs say AI might take our jobs, it might lighten our workloads, or it might put us into new jobs we didn't imagine. A recent Goldman Sachs report estimates that about 7% of workers will be displaced by AI over the next decade. Too anxious to wait until 2036, I wanted to see how close AI could get to taking my job as a reporter in 2026 — hoping it was many, many years away.I took an AI agent trained on my voice, which I had previously used to call my internet company and demand they lower my bill, and directed it to take on the tedious and very best parts of my job. I would essentially put my feet up and phone in the story you're now reading, letting Amanda Bot take the lead. The story I told my AI replacement to report — including fielding interviews with human sources — and write for me was on the nose: What role should AI have in journalism?Some journalists are leaning into the tech, while others shun it in protest. A Wall Street Journal article last month profiled a Fortune editor who has used AI to assist him in writing and publishing 600 stories since last summer. Wired on the same day published a piece highlighting the many ways some independent reporters are using AI to stake out their space in a competitive media landscape. Business Insider has produced stories with AI bylines. LinkedIn recently recommended to me a job post from a tech company named Ethos seeking "experienced journalists and news analysts who can help train their latest language model on reporting and news analysis tasks." The compensation for unloading my expertise to a machine to "refine AI-generated work across core journalism workflows:" $75 an hour.My experiment involved testing the limits of several AI tools. I used Claude to analyze my work at Business Insider, with some guidance from deepfake detection company Reality Defender. The chatbot parsed my style into bulleted points, summarizing what I've written in passing about my friendships, relative age, where I live, and assumed "she is single" based on a story I wrote about in-person meet-cutes coming back into vogue. The model also picked ...
How Contact Center AI Is Affecting the State of Agent Experience
What is agent experience in a contact center? Agent experience refers to the quality of a contact center agent's day‑to‑day work, shaped by the tools, systems, workflows, and AI that they use. Great agent experience minimizes unnecessary manual tasks, provides scheduling flexibility and helps agents resolve issues efficiently.
The missing ingredient in enterprise agents: a living map of how work ...
Pilots launch fast. But the hard part is: most companies aren't set up for agents to succeed. This isn't because the models aren't good enough, but because the agents don't have the one ingredient they need to operate inside your business. They need a living, accurate description of how work actually happens across teams and tools.
