​I'm re-reading Gardner Read's Music Notation from 1974. I bought my copy in 1977, which makes me 16 at the time – old enough to take it seriously, young enough to believe comprehensive understanding was achievable through diligent study. Later, this book would influence Igor Engraver's formatting decisions, though not always in ways I'd care to defend today.

What strikes me now is what Read doesn't cover. There's nothing about ledger line thicknesses, actual distances in spaces between noteheads and accidentals, sit-straddle-hang rules, slur curvatures, or tie formatting. None of the engraver-level detail that Elaine Gould's Behind Bars (2011) and Ted Ross's The Art of Music Engraving & Processing (1970, but I didn't discover it until much later) document so comprehensively. Read gives you musical orthography – what symbols mean and when to use them – but not typographical execution.

​When Magnus Johansson published examples of Igor's output on NOTATIO recently, I experienced that particular species of discomfort that comes from seeing your 25-year-old work through 2025 eyes. The ledger line thicknesses were wrong. The beam slants were inconsistent. We clearly knew nothing about sit-straddle-hang.

So what made Igor well-received? Not typographical perfection, that's certain.

First, integrated parts. Only Composer's Mosaic had them at the time, and Igor had them long before Finale or Sibelius. This alone solved a workflow problem that cost professional copyists days of manual labour.

Second, the user experience didn't fight the music. After spending years with Finale on The Maids – full score, parts, piano reduction – I ended up hating Finale. I've called it 'as user-friendly as a cactus' more than once. Creating something that didn't actively work against the creative process was evidently a sufficient innovation.

Third, note entry was fast and powerful. The modal Flow Mode interface that would later vanish completely from notation software for 23 years gave professional users substantial note entry and editing speed improvements. When you're saving many hours per score, you'll forgive a few ledger lines being slightly too thin – and there was a setting for that anyway.

Fourth, we had stellar MIDI playback and a semantic model that made things consistent rather than a collection of rules-of-thumb. That alone provided predictability. And everything could be adjusted – the absence of automatic sit-straddle-hang rules just meant more manual interventions.

The landscape in 1996 made these trade-offs reasonable. The streamlined experience outweighed what we today immediately see was missing.

​2025 is not 1996.

The leading programs have improved considerably since 1996. They're genuinely competent at beam placement and formatting – not flawless, but competent enough that egregious errors are rare.

A new program entering this landscape must get the foundations correct from day one. Beam placement, slurs, ties, accidental positioning – these must be flawless, not 'good enough to ship'. The field has progressed, and users' baseline expectations have risen accordingly.

This is as it should be. But there's something deeper that hasn't been solved.

Here's what I've stated repeatedly: Ooloi is not about 'disruption' or market share. The entire motivation is to escape what commercialism leads to and create something modern, scalable, and architecturally correct from the ground up. Why? Because music notation is an extremely messy and difficult field of computation, and it requires correctness to address its long-standing problems of scalability and accuracy.

This starts with internal representation.

The old programs – and many modern ones still in broad use – were all based on a paradigm inherited from MIDI. MIDI was the standard for pitch representation at the time, and all notation software needed MIDI output for playback anyway. This meant pitches were MIDI numbers (0-127) with attachments indicating whether they were sharp or flat. Figuring out musical context – for instance, to determine what accidentals to draw – had to be derived from something with no connection to musical structure whatsoever. It had to be inferred from context each time.
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That's at the root of the problems programs still have with accidentals. The internal representation is designed around the presentation – the visual aspect – not around the meaning, the semantics, of the music.

And of course, MIDI has no concept of microtonality, which is why notation programs struggle with microtonal entry, presentation, and playback.

Furthermore, for duration, these early programs based their rhythmic representation on a raster of 480 subdivisions – ticks – of a quarter note (TPQN: Ticks Per Quarter Note). A quarter note is 480 ticks long in some arbitrary tempo, an eighth is 240, and so forth. This is the equivalent of pixels in a JPEG, which means there's a limit to what the raster can represent.

The number 480 isn't evenly divisible by very many factors. This leads to all the problems we're still seeing in music notation programs. Various kinds of duct tape – rules of thumb, arbitrary rounding, tolerance spans – have to be used. When tuplets are nested, the approximation errors compound. We're still seeing the effects of this unfortunate MIDI heritage in 2025.

A MIDI-derived representation centred on presentation – the visual aspect – will always have difficulty interpreting what the music means. That interpretive layer is essential for presenting it correctly and consistently.

For that, you need a semantic model, which turns this on its head. The representation is 'musically correct' and detached from its presentation. Once this is in place, you can make informed decisions instead of relying on rounding and rules-of-thumb. It also makes things like playback trivial, which in MIDI-based systems is paradoxically complex.
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​Igor Engraver was, I believe, one of the first programs – possibly the very first – to use a fully semantic internal model. It was also the first to model the real world by using Musicians playing Instruments, which allowed new and powerful abstractions.

It's interesting that Dorico also has this arrangement, though they call their Musicians 'Players' – but it's the same thing. I have no idea whether Daniel Spreadbury was inspired by Igor here, but it's not unlikely. On the other hand, introducing Musicians/Players into the representational hierarchy is a logical choice once you commit to semantic modelling.

I'm not certain Dorico has a fully semantic model, though it's closer than any other program I know of. LilyPond doesn't, despite its sophisticated batch nature. One telling diagnostic: look at how they handle remembered accidentals for grace notes, and how they treat them rhythmically. Another: how durations are represented. If they're floating-point numbers, they're approximations. For true accuracy in all situations, you need rational numbers – infinite precision, always correct. Anything else eventually leads to problems.

If a program has problems with edge cases or behaves inconsistently when dragging things cross-staff, check how it represents pitch and duration. If floating-point is involved, or rasters of ticks (480 or otherwise), the representation isn't semantic. The program might still handle 95% of hairy accidental placements competently. But when it starts having problems with tied notes across key changes or grace notes at measure starts, you know rules-of-thumb are involved – which means results can never be fully deterministic.

Ooloi is fully semantic with the explicit intention of making results fully deterministic.

This might not matter if you're satisfied with what capable commercial programs achieve today. That's legitimate – they handle about 95% of cases well. But if you depend on the remaining 5%, or if you spend your days as an engraver adjusting those 5% repeatedly, then you understand what I mean by deterministic results saving considerable time.

Now, on to Gould and Ross – books that weren't available when Igor was created. We'd inevitably have implemented their specifications had we had time. But as you know, I was ousted from my own company by venture capital pop zombies before we could. They thought guitar tablature was more important than correct engraver-level beaming.

This time, there will be no guitar tablature at the expense of correct beaming and orthography. All things in their proper order. Lead sheets are kid's stuff, comparatively speaking, and will be added later as plugins.

​I'm one of the world's most committed anti-religious people. Despite decades at organ consoles in churches and cathedrals, I stand with Hitchens: religion is humanity's adolescent phase, something we need to outgrow. Its influence is fundamentally harmful.

But when I read something like How Lisp Became God's Own Programming Language, I completely understand the reverence the author describes. There's something about Lisp – and Clojure – that creates what you can only call a transcendental response. Nothing actually transcendental happens, of course, but the feeling is real.

What Lisp gives you is freedom. I've written about 'windsurfing through parentheses' before, and the metaphor sticks because it captures something essential. Most programmers are chained to the oars of enterprise slave galleys, with CTOs yelling 'RAMMING SPEED!' like that brilliant scene from Ben-Hur. Meanwhile, those of us who've found Lisp are windsurfing in circles around them, enjoying a freedom they can barely imagine.

The discovery feels like Dave Bowman meeting the monolith: 'My God... it's full of stars!' That vertigo when you realise this thing's inner dimensions vastly exceed its outer ones. Lisp isn't transcendental, but it works like a star gate in both senses. The language doesn't get in your way, and it opens new ways of thinking. At the same time, it's so simple that complexity becomes manageable.

I remember that August 1979 BYTE magazine perfectly. The cover promised mysteries, the articles delivered. I couldn't wait to start implementing what they described – eventually doing it in 6502 assembler, using an assembler I'd written in BASIC.

Everything clicked, even as a teenager. This was real freedom, expressed as code.

Years later, I wrote HotLisp (or 'HotLips' – M.A.S.H. was huge then) for the Royal College of Music in Stockholm. It was incredibly ambitious: a full Common Lisp that treated MIDI events as first-class citizens. Looking back, I see this as the beginning of what became Igor Engraver – integrating music directly into the computational core. We used it to control our Synclavier and MIDI synths whilst teaching algorithmic composition to advanced students at the Royal Academy.

The Two-Bit History article nails something important about Lisp's mystique. It traces the evolution from McCarthy's 'elegant mathematical system' through AI research, Lisp machines, and SICP's role in making it the language that 'teaches you programming's hidden secrets'. Each phase built the reputation.

What the article doesn't cover is the educational betrayal that followed. Computer science departments got it right for a while – they taught Scheme as a first language because it let students focus on learning algorithms rather than wrestling with syntax. Pure freedom to think about problems. Then Java Enterprise was foisted upon the world, the departments caved in, and they started churning out galley slaves instead of computer scientists. I see this as nothing short of high treason.

But here's what really matters: that freedom has evolved in Clojure. Rich Hickey didn't just bring Lisp to the JVM – he solved problems that even Common Lisp couldn't handle elegantly. Those immutable data structures aren't academic toys; they're game changers that eliminate whole categories of bugs whilst making concurrency and parallelism natural instead of terrifying. The effects ripple out: undo/redo becomes trivial, and the JVM gives genuine multi-platform reach.

This isn't just improvement – it's architectural breakthrough disguised as evolution. Clojure keeps Lisp's essential quality (that feeling of discovering how programming should work) whilst solving modern problems McCarthy couldn't have anticipated.

The poor souls in corporate Java shops keep rowing, occasionally granted small mercies as functional concepts trickle in – hints of the freedom they're missing.

I wish they could experience what we know: programming doesn't have to feel like industrial labour. There's a way of working where ideas flow directly into code, where the language becomes transparent, where you stop fighting tools and start windsurfing through solutions.

Maybe that's the point. As McCarthy noted in 1980, Lisp survives not because programmers grudgingly accept it as the best tool for each job, but because it hits 'some kind of local optimum in programming language space'. It endures even though most programmers never touch it, sustained by reports from those who've experienced its particular form of computational enlightenment.

Until we can imagine God creating the world with some newer language – and I doubt that day is coming soon – Lisp isn't going anywhere.

Read the full article at Two-Bit History: https://twobithistory.org/2018/10/14/lisp.html

Yesterday’s post was about pitch transposition in Ooloi: how an old Igor Engraver function (printed on a t-shirt, of all places) came back to life in a new context. That work didn’t just solve the mechanics of shifting notes up and down; it reopened the larger question of playback. How do you hear microtonality and advanced humanisation without drowning in technical workarounds?

In Igor, the answer was MIDI. Notes were split across channels, bent into place, reassigned constantly. The result worked, but at the cost of complexity: a “DNA soup” of allocations and pitch-bend tricks. Ingenious, but exhausting.

Ooloi makes a different choice.

With ADR-0027: Plugin-Based Audio Architecture, we draw a line: no MIDI output in the core, no audio generation in the backend. Playback is done entirely through plugins in the frontend. If you want VST/AU instruments, SoundFonts, OSC, or any other output path, you install a plugin. The backend remains what it should be: musical data, collaboration, structure.

This is not just simplification, it’s liberation.

• Microtonality is handled directly in the data model, then played back by plugins without channel gymnastics.
• Humanisation is no longer bound to 7-bit controllers; plugins can drive modern sample libraries with full parameter precision.
• Collaboration becomes clearer: the backend never streams audio, never mangles MIDI, never compromises. Each client handles its own sound.

Put bluntly: we no longer need MIDI as an output protocol. It served its time. For professionals who need nuanced playback, orchestral realism, or contemporary techniques, we now have better tools: VST/AU plugins and beyond.

That said, MIDI output isn’t forbidden. If anyone needs it, a frontend plugin can provide it. For tonal music it will work fine. But if you want advanced humanisation or microtonality, you’ll inherit the need for all the old machinery: channel allocation, pitch-bend acrobatics, the DNA soup. That’s exactly why Ooloi itself doesn’t touch it.

The logic is simple: Ooloi’s core manages music, not sound. Plugins handle playback, and in doing so, they do it better than MIDI ever could.

The DNA soup is gone. What remains is clean, modern, and far more powerful.

​Our solution was elegantly brutal: we seized complete control of attached MIDI units and employed pitch bend to achieve microtonal accuracy. This required distributing notes across MIDI channels according to their pitch bend requirements, using register allocation algorithms borrowed from compiler technology. In a chord containing one microtonally altered note, that note would play on a different channel from its companions. We changed patches frantically and maintained no fixed relationship between instruments and channels – everything existed in a kind of 'DNA soup' where resources were allocated dynamically as needed.

This approach let us extract far more than the nominal sixteen-channel limit from typical MIDI synthesisers. We maintained detailed specifications for every common synthesiser on the market, including how to balance dynamics and handle idiosyncratic behaviours. 

​The system's sophistication extended well beyond pure pitch calculations. When my opera The Maids was commissioned by the Royal Stockholm Opera, I spent considerable time crafting realistic rehearsal tapes. Everything I learned from that process was automated into Igor's playback engine.

We also collaborated with the KTH Royal Institute of Technology Musical Acoustics department, led by the legendary Johan Sundberg, whose research had quantified subtle but crucial performance characteristics. Those famous four milliseconds – the consistent temporal offset between soloists and accompaniment in professional orchestras – found their way into our algorithms. Such details proved particularly effective with Schönberg's Hauptstimme markings (𝆦) or similar solo indicators.

We also developed what my composer colleague Anders Hillborg and I privately called 'first performance prophylaxis' – a deliciously cruel setting that simulated the sound of musicians who hadn't practiced. In other words, the kind of sound landscape any composer is used to hearing at a first orchestral rehearsal of a new piece and which always makes you doubt your own talent. Turn this setting up, and you'd hear a characteristically dreadful youth orchestra. Turn it down completely, and you'd get the robotic precision that plagued every other MIDI system. Rather like Karl Richter's Baroque organ recordings.

The humanisation algorithms incorporated realistic instrumental limitations. Passages written too quickly for an instrument would skip notes convincingly. We modelled the typical rhythmic hierarchy of orchestral sections: percussion most precise, then brass, then woodwinds, with strings bringing up the rear. Instruments were panned to their proper orchestral seating positions. Piccolo trills were faster than tuba trills. The result was startlingly realistic, particularly by 1996 standards.

​Now, twenty-five years later, that laundry basket discovery has culminated in ADR 0026: Pitch Representation and Operations, documenting Ooloi's comprehensive pitch representation system. The original Common Lisp has been reborn as Clojure code, with string-based pitch notation ("C#4+25") serving as the canonical format and a factory-based transposition system supporting both chromatic and diatonic modes.

The string representation offers several advantages: compact memory usage for large orchestral scores, direct human readability for debugging, and seamless integration with parsing and caching systems. Most crucially, it supports arbitrary microtonal deviations, something that remains problematic in most contemporary notation software.

The factory pattern generates specialised transposition functions that encapsulate their musical behavior rules through closures. Rather than repeatedly passing configuration parameters, the factory creates efficient, composable functions that understand their specific musical contexts. A diatonic transposer preserves letter-name relationships; a chromatic transposer produces frequency-accurate results with canonical spellings.

The t-shirt in my laundry basket represented more than nostalgic memorabilia; it was unfinished business. That higher-order function embodied a sophisticated understanding of musical mathematics that took a long time to develop and seconds for an AI to recognise as architecturally significant.

Now, with Ooloi's pitch operations properly documented and implemented, that business approaches completion. The code has evolved from promotional garment to production system, carrying forward those insights from 25 years ago into a new, modern technological context.

It's exciting. And still a little unnerving.