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Autism through talent
DEVELOPED WITH PARTICIPANT
Lee McKeeman
Learning about yourself and how to support yourself can be really powerful.
LEE MCKEEMAN
As a teenager, Lee McKeeman built his own computers, piece by piece, on his bedroom floor. He taught himself HTML and made websites for his friends. Computing became what he now calls his special interest. Later, so did software.
He didn't know where that interest would take him. He also didn't know why he felt different in so many other parts of life.
"I just thought I was a weird kid," he says.
Around age ten or eleven, teachers described him as disruptive, and Lee was diagnosed with what was then called ADD. From his side, most of it was jokes, silliness, moving around in his seat, trying to make other kids laugh. He wanted to be included.
His parents were offered medication. Lee was young and unsure about it, so instead he worked on changing his own behavior. He got quieter. The adults around him seemed satisfied.
Years later, he understood that effort differently: as masking. He had learned to act in ways that made other people comfortable, without knowing why it left him so drained.
Some of what looked like distraction was actually helping him focus. When Lee did homework with a television playing quietly in the background, his mother assumed it was pulling his attention away. For Lee, it was the opposite. The background sound gave part of his mind something to process, which made it easier to stay on the main task. He tapped his pencil, moved his legs, sometimes needed to sit somewhere different in the classroom. He had no word for any of this at the time. He just knew it helped.
His grades made the harder parts invisible. He did well in school, took advanced classes, and scored well on standardized tests. Once the disruptive behavior faded, adults mostly saw a strong student.
"Everything was not fine," he says now. "I was struggling in a lot of ways.There’s not an autism fix, and it doesn’t need to be fixed. But it does need to be supported.’’
That pattern followed him into his first job. Competence became his way of belonging.
He didn't know where that interest would take him. He also didn't know why he felt different in so many other parts of life.
"I just thought I was a weird kid," he says.
Around age ten or eleven, teachers described him as disruptive, and Lee was diagnosed with what was then called ADD. From his side, most of it was jokes, silliness, moving around in his seat, trying to make other kids laugh. He wanted to be included.
His parents were offered medication. Lee was young and unsure about it, so instead he worked on changing his own behavior. He got quieter. The adults around him seemed satisfied.
Years later, he understood that effort differently: as masking. He had learned to act in ways that made other people comfortable, without knowing why it left him so drained.
Some of what looked like distraction was actually helping him focus. When Lee did homework with a television playing quietly in the background, his mother assumed it was pulling his attention away. For Lee, it was the opposite. The background sound gave part of his mind something to process, which made it easier to stay on the main task. He tapped his pencil, moved his legs, sometimes needed to sit somewhere different in the classroom. He had no word for any of this at the time. He just knew it helped.
His grades made the harder parts invisible. He did well in school, took advanced classes, and scored well on standardized tests. Once the disruptive behavior faded, adults mostly saw a strong student.
"Everything was not fine," he says now. "I was struggling in a lot of ways.There’s not an autism fix, and it doesn’t need to be fixed. But it does need to be supported.’’
That pattern followed him into his first job. Competence became his way of belonging.
"If I'm very competent, then I will be of value to a group," he remembers thinking. "And if I'm of value to a group, I won't be made to leave it, even if I'm a little unusual."
That path almost skipped Amazon entirely. In 2012, a recruiter reached out about a job there. Lee didn't think he had a real shot. His then-wife pushed him to at least look into it. He applied, got the job, and stayed almost nine years.
The work itself kept changing. He helped launch one of the first Prime Video apps for iPad, then moved on to the Fire Phone, then worked on taking Prime Video into new countries around the world. Colleagues nicknamed him "Mad Dog," because once he had a technical problem in front of him, he wouldn't let go, even when the cause turned out to sit inside a compiler or an operating system, well outside his own team's code.
As his reputation grew, people also got more comfortable with the rest of him: the spinning in his chair, sitting in unexpected spots, moving around the office while he worked. He noticed the connection later. If he'd been an average performer, "a little strange" might have been the main thing people remembered about him. Because he was seen as a strong engineer, the same habits just read as harmless quirks.
Along the way he became a Software Development Manager, and later a Bar Raiser, one of the interviewers trusted with real say in who gets hired across the company. Of everything he did at Amazon, he's said becoming a Bar Raiser was one of the most important parts.
That path almost skipped Amazon entirely. In 2012, a recruiter reached out about a job there. Lee didn't think he had a real shot. His then-wife pushed him to at least look into it. He applied, got the job, and stayed almost nine years.
The work itself kept changing. He helped launch one of the first Prime Video apps for iPad, then moved on to the Fire Phone, then worked on taking Prime Video into new countries around the world. Colleagues nicknamed him "Mad Dog," because once he had a technical problem in front of him, he wouldn't let go, even when the cause turned out to sit inside a compiler or an operating system, well outside his own team's code.
As his reputation grew, people also got more comfortable with the rest of him: the spinning in his chair, sitting in unexpected spots, moving around the office while he worked. He noticed the connection later. If he'd been an average performer, "a little strange" might have been the main thing people remembered about him. Because he was seen as a strong engineer, the same habits just read as harmless quirks.
Along the way he became a Software Development Manager, and later a Bar Raiser, one of the interviewers trusted with real say in who gets hired across the company. Of everything he did at Amazon, he's said becoming a Bar Raiser was one of the most important parts.
The technical side kept making more sense to him than everything around it. He assumed strong work would speak for itself; over time he learned that visibility, relationships, and plain self-advocacy mattered just as much. He also had to relearn how he gave feedback. His instinct, when he spotted a problem, was to just say so, directly. If he were wrong, he'd want someone to tell him the same way. Not everyone heard it that way.
"I had to learn that being right is not helpful if the way that you present something cannot be heard by your target audience," he says.
The person who first put a name to any of this wasn't a doctor. It was a relative of his wife's, who recognized certain traits in Lee and said so, plainly. He started reading about autism on his own. The more he read, the more he wanted a real evaluation, not just a guess. Finding a specialist who tests adults turned out to be harder than he expected.
He finally got evaluated in his late thirties, while working as a software engineer at Meta. Two answers came back at once: autism, and a sensory processing disorder.
Meta was hard on him in its own way. He'd raised concerns about how some experiments were being measured, and while people in data science tended to agree with him, saying it over and over didn't earn him trust inside his own team.
"I'm not saying I did it wrong," he says, "but I didn't do it in a way that could be heard."
He'd also joined during the pandemic, onboarding fully remote, and spent months trying to get matched to a team. Nine years of learning Amazon's unwritten rules turned out to count for very little somewhere else. In a podcast interview, he put it simply: he "didn't have a great time there." On LinkedIn, he was even more direct: "I did not succeed at Meta."
At Google, the technical side went well; he reached Staff Engineer. But a new problem showed up: expectations that were too vague to act on. A manager might say "do more of this" or "do less of that," and Lee would make what seemed to him a reasonable adjustment, only to find out later that far more had been expected. At one point that gap put his job at risk. What actually turned things around was a performance improvement plan with real numbers attached: specific goals, dates, measurements. He met them, then went past them.
He also started describing his own output as "spiky": long stretches of research that produce almost nothing visible, followed by one large result. Left unexplained, that pattern can look like nothing is happening. Now he asks his managers directly, up front, which kind of task this is: keep investigating until he has the answer, or spend two days, report what he's found, and move on.
None of this followed a straight line from diagnosed to fixed. What helped was a collection of smaller things. At Google, he joined an employee group for autistic staff, where he could ask people a simple question: has this happened to you, and what did you do about it? He worked with occupational therapists, who helped him notice hunger, fatigue, and other signals that hyperfocus tends to bury. A manager once suggested he add a short TL;DR to the top of his messages, since Lee tends to over-explain things, wanting to be fully understood. It helped. These days he also turns off Slack notifications when he needs to focus and protects meeting-free stretches for deep work.
At Netflix, where he works now, clarity showed up from day one. New hires get a rough outline of what they should accomplish in their first week, first month, first quarter. For Lee, that's been steadying; he can check the outline and know where he stands. He compares it to a curb cut in a sidewalk: built for wheelchair users, but useful to anyone pushing a stroller or pulling a suitcase. Clear expectations work the same way. They may matter most for autistic employees, but they make things easier for almost everyone.
McKeeman speaks publicly now about both sides of his career, engineering and autism.
"I had to learn that being right is not helpful if the way that you present something cannot be heard by your target audience," he says.
The person who first put a name to any of this wasn't a doctor. It was a relative of his wife's, who recognized certain traits in Lee and said so, plainly. He started reading about autism on his own. The more he read, the more he wanted a real evaluation, not just a guess. Finding a specialist who tests adults turned out to be harder than he expected.
He finally got evaluated in his late thirties, while working as a software engineer at Meta. Two answers came back at once: autism, and a sensory processing disorder.
Meta was hard on him in its own way. He'd raised concerns about how some experiments were being measured, and while people in data science tended to agree with him, saying it over and over didn't earn him trust inside his own team.
"I'm not saying I did it wrong," he says, "but I didn't do it in a way that could be heard."
He'd also joined during the pandemic, onboarding fully remote, and spent months trying to get matched to a team. Nine years of learning Amazon's unwritten rules turned out to count for very little somewhere else. In a podcast interview, he put it simply: he "didn't have a great time there." On LinkedIn, he was even more direct: "I did not succeed at Meta."
At Google, the technical side went well; he reached Staff Engineer. But a new problem showed up: expectations that were too vague to act on. A manager might say "do more of this" or "do less of that," and Lee would make what seemed to him a reasonable adjustment, only to find out later that far more had been expected. At one point that gap put his job at risk. What actually turned things around was a performance improvement plan with real numbers attached: specific goals, dates, measurements. He met them, then went past them.
He also started describing his own output as "spiky": long stretches of research that produce almost nothing visible, followed by one large result. Left unexplained, that pattern can look like nothing is happening. Now he asks his managers directly, up front, which kind of task this is: keep investigating until he has the answer, or spend two days, report what he's found, and move on.
None of this followed a straight line from diagnosed to fixed. What helped was a collection of smaller things. At Google, he joined an employee group for autistic staff, where he could ask people a simple question: has this happened to you, and what did you do about it? He worked with occupational therapists, who helped him notice hunger, fatigue, and other signals that hyperfocus tends to bury. A manager once suggested he add a short TL;DR to the top of his messages, since Lee tends to over-explain things, wanting to be fully understood. It helped. These days he also turns off Slack notifications when he needs to focus and protects meeting-free stretches for deep work.
At Netflix, where he works now, clarity showed up from day one. New hires get a rough outline of what they should accomplish in their first week, first month, first quarter. For Lee, that's been steadying; he can check the outline and know where he stands. He compares it to a curb cut in a sidewalk: built for wheelchair users, but useful to anyone pushing a stroller or pulling a suitcase. Clear expectations work the same way. They may matter most for autistic employees, but they make things easier for almost everyone.
McKeeman speaks publicly now about both sides of his career, engineering and autism.
Engineer to Manager and Back Again: Interview With Lee McKeeman
His talks include An Autistic Journey to Google Staff Engineer and Autism Allyship and Identity in Tech, and he's joined panels on what it actually takes to reach Staff-level engineering. He writes about the same things on his Substack, Cognition and Coding, and to close to 28,000 people on LinkedIn.
He knows the seniority he's built gives him a kind of safety that a lot of autistic people don't have, and he uses it to talk about the things that stay hidden behind a good résumé, good grades, strong performance reviews. He also talks about interviewing candidates at Amazon, and pushing back when someone was marked down for not making eye contact: does that actually affect their ability to do the job, he'd ask, or is it just not how they show they're paying attention?
Lee is also a father of five. He and his wife Jill married in 2017, and their family later welcomed twins.
Lee is also a father of five. He and his wife Jill married in 2017, and their family later welcomed twins.
His advice to autistic people: figure out how your own mind works, notice what kind of problem holds your attention, and look for a place that knows what to do with that.
