Monte Carlo Integration
Suppose we want to measure the area of a circle. Yeah, yeah, you already know this, it’s \( \pi r^2 \), but let’s say we want to measure a circle of radius 1 with something called Monte Carlo integration:
- We generate pairs \( (x,y) \) where \( x \) and \( y \) are independent and uniformly distributed between 0 and 1.
- We count the fraction of pairs \( (x,y) \) that are inside our circle, by testing each one: the point \( (x,y) \) is inside the circle if \( x^2 + y^2 < 1...
Stuck with Jira — and Stuckons
Jason Sachs vents about Jira’s quirks and why it still feels stuck despite years of fixes. He walks through concrete pain points: nonstandard markup, relentless notification noise, poor meta-task support, and limited analytics that make day-to-day engineering work harder. To explain why schedules blow up, he introduces a simple kepton model of planons, workons, and stuckons that highlights unexpected work.
Baking in Process Improvements
Jason Sachs uses a backyard cookie-baking session with his niece to illustrate practical process improvements engineers can apply. He documents batch-by-batch tweaks — temperature, dough placement, and a pipelined scooping step — that raised throughput and improved quality, then connects the lesson to pilot projects and small automations like a Python script for JIRA. The piece makes the case for quick experiments and a culture that rewards refinement.
Beware of Analog Switch Leakage Current
Leakage currents in analog switches can quietly wreck precision reference circuits at elevated temperature. Jason M. Sachs walks through three switch-topology implementations for a switchable 1.25 V reference and shows which topology gives the smallest worst-case output error using real part specs. He explains why op amp input bias is usually negligible and gives practical fixes: lower resistances, better switches, or limiting temperature range.
How to Analyze a Three-Op-Amp Instrumentation Amplifier
The three-op-amp instrumentation amplifier gives you high input impedance, improved net bandwidth, and much lower sensitivity to resistor mismatch than a single-op-amp differential stage. Jason M. Sachs walks through the algebra, numeric examples, and historical notes to show how the preamp isolates common-mode, why splitting gain boosts bandwidth, how overall gain can be set with one resistor, and what practical limits to watch.
Supply Chain Games: A Warning on Tariffs
Jason Sachs warns that the 2025 tariff surge could amplify an existing semiconductor inventory glut and destabilize automotive and industrial supply chains. He lays out why steep, rapid tariff changes cannot be absorbed by years-long fab lead times, sticky proprietary ICs, or quick part substitutions. Read this to understand practical risks, likely timing, and what engineers and buyers should watch over the next two to three years.
Sheep Bridge: In Praise of Generalists and System Engineers
Jason Sachs makes the case for hiring generalists and valuing system engineers, because they do more than take a high-level view. He explains how multi-scale thinking, arbitration among subsystems, and clear visualization prevent integration failures, using concrete examples from battery-voltage tradeoffs, Sheep Bridge map lessons, and encoder signal checks. Read this for practical rules that keep embedded projects coherent.
Scorchers, Part 4: Burned by the Happy Path (Simon Says)
Designs that only work along the happy path break in real use, causing frustration and sometimes safety risks. Jason M. Sachs uses everyday examples from microwaves to car Auto Park logic to show how mutable software and physical state create brittle behavior. He outlines practical firmware fixes such as clear state machines, sensor or user-driven resynchronization, soft-start delays, and a ‘‘Drunken Happy Path’’ fuzzing approach to find real-world failure modes.
Lost Secrets of the H-Bridge, Part V: Gate Drives for Dummies
Learn the most important issues in power MOSFET and IGBT gate drives: - Transistor behavior during switching - Calculating turn-on and turn-off times - Passive components used between gate drive IC and transistor - Reverse recovery - Capacitively-coupled spurious turn-on - Factors that influence a good choice of turn-on and turn-off times - Gate drive supply voltage management - Bootstrap gate drives - Design issues impacting reliability
Turn It On Again: Modeling Power MOSFET Turn-On Dependence on Source Inductance
This is a short article explaining how to analyze part of the behavior of a power MOSFET during turn-on, and how it is influenced by the parasitic inductance at the source terminal. The brief qualitative reason that source inductance is undesirable is that it uses up voltage when current starts increasing during turn-on (remember, V = L dI/dt), voltage that would otherwise be available to turn the transistor on faster. But I want to show a quantitative approximation to understand the impact of additional source inductance, and I want to compare it to the effects of extra inductance at the gate or drain.
Chebyshev Approximation and How It Can Help You Save Money, Win Friends, and Influence People
Are expensive math libraries or huge lookup tables eating CPU and flash on your microcontroller? In this practical guide Jason Sachs shows how Chebyshev polynomial approximation (with range reduction, splitting, and small interpolated tables) can give near-minimax accuracy while using far less code and runtime. The post compares Taylor series, plain and interpolated tables, and explains how to fit empirical sensor data and evaluate coefficients efficiently.
Lost Secrets of the H-Bridge, Part V: Gate Drives for Dummies
Learn the most important issues in power MOSFET and IGBT gate drives: - Transistor behavior during switching - Calculating turn-on and turn-off times - Passive components used between gate drive IC and transistor - Reverse recovery - Capacitively-coupled spurious turn-on - Factors that influence a good choice of turn-on and turn-off times - Gate drive supply voltage management - Bootstrap gate drives - Design issues impacting reliability
Supply Chain Games: What Have We Learned From the Great Semiconductor Shortage of 2021? (Part 2)
Jason Sachs zooms through semiconductor history, fab economics, and the microcomputer era to explain why the 2021 chip shortage unfolded the way it did. He blends technical explainers on photolithography, yields, and node migration with business lessons about risky multi-year fab investments and cyclic demand. Engineers get historical case studies and practical signals to watch when designing products for greater supply resilience.
Supply Chain Games: What Have We Learned From the Great Semiconductor Shortage of 2021? (Part 3)
Jason Sachs pulls back the curtain on Moore's Law and the foundry business to explain why the semiconductor shortage exposed brittle economics. He traces how roadmaps, depreciation schedules, and node mix force foundries to juggle expensive new fabs and mature capacity, and shows why leading-edge nodes punch above their volume share in revenue. Engineers get practical insight into how capacity and timing decisions ripple through the supply chain.
Development of the MOS Technology 6502: A Historical Perspective
A tiny team at MOS Technology pulled off one of the most influential microprocessor wins of the 1970s, creating the 6502 by marrying clever circuit choices with pragmatic manufacturing techniques. This excerpt by Jason Sachs focuses on the NMOS depletion-load process, mask and layout workflows, and yield-improving tricks like Micralign projection lithography and spot-knocking, showing how engineering and process decisions made a low-cost CPU ubiquitous.
Understanding and Preventing Overflow (I Had Too Much to Add Last Night)
Integer overflow is stealthier than you think, and in embedded systems it can break control loops or corrupt data. Jason Sachs walks through the usual culprits, including addition, subtraction, multiplication, shifting and Q15 fixed-point traps, plus C-specific pitfalls such as undefined signed overflow and INT_MIN edge cases. He then lays out practical defenses: prefer fixed-width types, widen and saturate intermediates, enable wraparound where appropriate, and reason about modular congruence for compound arithmetic.
How to Analyze a Three-Op-Amp Instrumentation Amplifier
The three-op-amp instrumentation amplifier gives you high input impedance, improved net bandwidth, and much lower sensitivity to resistor mismatch than a single-op-amp differential stage. Jason M. Sachs walks through the algebra, numeric examples, and historical notes to show how the preamp isolates common-mode, why splitting gain boosts bandwidth, how overall gain can be set with one resistor, and what practical limits to watch.
How to Read a Power MOSFET Datasheet
Jason Sachs takes a soapbox to stop a recurring mistake: misreading power MOSFET datasheets. This practical guide separates marketing blurbs and typical graphs from the specifications you can actually rely on, and explains how to use RDS(on), VGS, gate charge, SOA and thermal data in real designs. Read this before you pick a MOSFET or size a gate driver.
Thermistor signal conditioning: Dos and Don'ts, Tips and Tricks
Jason Sachs shows how to keep thermistor conditioning simple and accurate for embedded systems. He warns against analog linearization and excessive analog stages, and explains why ratiometric dividers, proper ADC buffering, and using the same reference voltage give better results. The post also covers thermal pitfalls like self-heating and lead conduction, plus practical tips for ADC autocalibration and polynomial temperature conversion.
Supply Chain Games: What Have We Learned From the Great Semiconductor Shortage of 2021? (Part 5)
Most of the time a wafer spends in a fab is spent waiting in queues, not being processed. Jason Sachs peels back why cycle times stretch weeks to months, covering WIP accounting, die and wafer banks, the days per mask layer metric, and how variability and utilization tradeoffs turned fab behavior into a major factor in the 2021 chip shortage.
Chebyshev Approximation and How It Can Help You Save Money, Win Friends, and Influence People
Are expensive math libraries or huge lookup tables eating CPU and flash on your microcontroller? In this practical guide Jason Sachs shows how Chebyshev polynomial approximation (with range reduction, splitting, and small interpolated tables) can give near-minimax accuracy while using far less code and runtime. The post compares Taylor series, plain and interpolated tables, and explains how to fit empirical sensor data and evaluate coefficients efficiently.
How to Read a Power MOSFET Datasheet
Jason Sachs takes a soapbox to stop a recurring mistake: misreading power MOSFET datasheets. This practical guide separates marketing blurbs and typical graphs from the specifications you can actually rely on, and explains how to use RDS(on), VGS, gate charge, SOA and thermal data in real designs. Read this before you pick a MOSFET or size a gate driver.
Understanding and Preventing Overflow (I Had Too Much to Add Last Night)
Integer overflow is stealthier than you think, and in embedded systems it can break control loops or corrupt data. Jason Sachs walks through the usual culprits, including addition, subtraction, multiplication, shifting and Q15 fixed-point traps, plus C-specific pitfalls such as undefined signed overflow and INT_MIN edge cases. He then lays out practical defenses: prefer fixed-width types, widen and saturate intermediates, enable wraparound where appropriate, and reason about modular congruence for compound arithmetic.
Adventures in Signal Processing with Python
Jason Sachs shows how PyLab (numpy, scipy, matplotlib) can handle many signal-processing and visualization tasks engineers usually reach for MATLAB to do. He walks through practical examples including PWM ripple, two pole RC filters, and symbolic math with SymPy, and shares real-world installation tips and trade-offs. The post closes with pointers to IPython and pandas to speed interactive analysis and data handling.
How to Estimate Encoder Velocity Without Making Stupid Mistakes: Part I
Encoder velocity estimation is easy to get wrong, and Jason Sachs walks through the traps engineers fall into. He demolishes the common advice to time between encoder edges, shows how encoder quantization and state-width errors break that approach, and argues for fixed-rate sampling with sensible filtering for most control uses. Part II will cover more advanced estimators for higher performance needs.
Ten Little Algorithms, Part 2: The Single-Pole Low-Pass Filter
Jason Sachs shows how a single-pole IIR low-pass filter, implementable in one line y += alpha * (x - y), tames noise in embedded signals without floating point. The post explains how to compute alpha from tau and delta-t, practical tradeoffs like phase lag and oversampling, and fixed-point pitfalls including how many extra state bits you need to avoid quantization. Short, practical, and code-ready.
Thermistor signal conditioning: Dos and Don'ts, Tips and Tricks
Jason Sachs shows how to keep thermistor conditioning simple and accurate for embedded systems. He warns against analog linearization and excessive analog stages, and explains why ratiometric dividers, proper ADC buffering, and using the same reference voltage give better results. The post also covers thermal pitfalls like self-heating and lead conduction, plus practical tips for ADC autocalibration and polynomial temperature conversion.
My Love-Hate Relationship with Stack Overflow: Arthur S., Arthur T., and the Soup Nazi
Jason Sachs traces his decade-long relationship with Stack Overflow, celebrating its fast answers, polished UI, and massive searchable archive while calling out a growing culture of harsh moderation. He argues strict, quality-first closures and inflexible automation often alienate newcomers and block helpful short-term answers. The post urges kinder handling of gray-area questions and smarter automation to keep the site useful and welcoming.
Zebras Hate You For No Reason: Why Amdahl's Law is Misleading in a World of Cats (And Maybe in Ours Too)
Amdahl’s Law is a useful warning, but Jason Sachs argues it can be misleading if you stop at the equation. Using the Kittens Game as a playful model, he shows how Gustafson’s perspective, positive feedback loops, and system-level synergy can turn modest component speedups into big real-world wins. The article closes with concrete embedded-systems examples like ISR timing and developer productivity.
Important Programming Concepts (Even on Embedded Systems) Part I: Idempotence
Idempotence is a simple design principle that prevents duplicate effects when operations are retried or repeated. Jason Sachs shows why it matters in embedded systems, from HTTP submit buttons and capacitive touch inputs to garage-door remotes and SPI DAC writes. Read this post to learn three practical idempotent techniques and when redundant writes are a sensible reliability trade-off.
